Good morning. Volkswagen has topped the Fortune 500 Europe for a third straight year, even as the auto industry it leads gets squeezed by tariffs and Chinese competition. The automaker’s revenue still climbed 3.4%, to more than $363 billion, in the fourth edition of Fortune’s ranking of Europe’s largest companies by revenue.

The combined revenues of the companies on the list hit a record high of $15.5 trillion this year. Profits rose 3% to just over $1 trillion, rebounding from a 5% decline in 2025.

Across the Fortune 500 Europe, margins have narrowed for two years running, falling to 6.5% from a high of 7.1% on the 2024 list—despite record revenue and profit growth. That’s consistent with stagflation pressures weighing on Europe’s corporate sector, Guido Cozzi, a macroeconomics professor at the University of St. Gallen, told Fortune’s Sam Birchall.

Three sectors generate over half of all revenue on the list: financials (24%), energy (20%), and motor vehicles and parts (10%). Finance remains Europe’s most dominant sector by revenue, profit, and headcount. A total of 105 finance companies earned a spot in the rankings, together generating 24% of the list’s total revenue, with Banco Santander (No. 9) and BNP Paribas (No. 10) in the top 10.

Financial companies also account for 40% of the list’s profit and employ 14% of its workforce. HSBC (No. 11) is the most profitable company on the list, recording $22 billion in profits for 2025 and one of only 25 companies to generate more than $10 billion in profits.

Europe’s finance-sector prominence stems from its biggest banks’ global reach and technical sophistication, Howard Yu, a professor at IMD Business School, told Birchall. Their decades-long presence in emerging markets gives them a depth few global rivals can match, he argues, calling it “a genuine strategic edge.”

Energy companies generate 14% of the list’s overall profit, and the sector ranks second to financials in employment. Another notable finding: BP is the only top-10 company with a woman CEO, Meg O’Neill. She’s also No.16 on this year’s Fortune Most Powerful Women (MPW) list. When O’Neill took over as CEO on April 1, she became the first woman to lead one of the five major oil companies.

BP is also the only one of its peers with women in both the CEO and CFO roles. Kate Thomson became BP’s finance chief in February 2024 after serving as interim CFO, making her the first woman to hold the role at the company. At Shell, No. 2 on the Fortune 500 Europe list, Sinead Gorman has served as CFO since April 2022. Gorman also earned a spot on this year’s MPW list.

Sheryl Estrada
Sheryl.Estrada@fortune.com

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While military action in Iran has dragged on longer than the White House initially estimated, President Trump is still insistent that, in the grand scheme of things, the conflict doesn’t even constitute a war.

But the cost of the military intervention—discounting the broader macroeconomic effects arising from supply chain upheaval—is still high, and growing. A new report from the Congressional Budget Office (CBO) released yesterday found that as of August 1, 2026, the armed conflict with Iran has cost the Department of Defense approximately $38 billion.

These funds reflect the cost of replacing expended munitions and equipment lost in battle, the CBO wrote, as well as increased flying hours, increased fuel costs, and “other operations.”

The estimate doesn’t include spending already budgeted for, such as the basic running costs of the military involved in the conflict. It also doesn’t take into account increased costs for other parts of the federal government, such as increased fuel prices paid by the postal service.

The total sum is also likely to have risen meaningfully since the beginning of August. If the conflict persists, the CBO notes, costs will increase: slowly if the level of violence remains low, but more rapidly if tensions escalate as they did in July.

If tensions are relatively muted—as they were in May and June—the action would require roughly $2 billion per month in financing. If tensions were to escalate to the levels seen later in the summer, this would rise to $3 billion a month—and higher if the conflict spiraled beyond levels currently seen.

The cost of the conflict thus far has come in below the additional sum the White House requested in June to fund the action. The CBO said the administration requested $87.6 billion in supplemental appropriations, of which $67.1 billion was to be funneled into the Department of Defense. “The portion of that request that appears to be directly related to the conflict, $42.3 billion, is about 10% larger than CBO’s estimate of DoD’s costs,” the CBO noted.

Indeed, the CBO’s estimates are roughly on par with (if not below) other reports. Defense Secretary Pete Hegseth said in July that the war had thus far cost $37.5 billion, while The Hill reported this week that the Pentagon’s latest update to Congress was that the conflict now totalled $42 billion.

Broader economic costs

President Trump has been keen to downplay the magnitude the Middle East conflict is having on America.

Trump defended Vice President J.D. Vance’s position that the conflict doesn’t warrant being called a war. Trump told reporters earlier this month: “A lot of people don’t call it a war, I call it a military conflict because it’s small potatoes for us, it’s not a thing.”

Trump highlighted that while 18 U.S. service members have died in the conflict, this is significantly lower than wars in recent memory—and described the strikes as “intermittent.” The CBO echoed that “relatively few U.S. forces have been involved compared with the much larger and longer U.S. operations in Iraq and Afghanistan.”

However, the financial costs to the federal budget and households are significant. In June, Moody’s estimated the cost to consumers for the Iran war is $750 a household—or $100 billion. Much of those extra costs have been passed on to households in the form of increased military spending and higher prices from oil supply disruption, according to Mark Zandi, chief economist at Moody’s Analytics.

This story was originally featured on Fortune.com

In a factory in Vantaa, a city in southern Finland, scientists and engineers are working on a groundbreaking innovation that converts carbon dioxide and hydrogen into a protein powder called Solein. The mustard-yellow powder, developed by Solar Foods, can be used in protein shakes and bars, pasta, and meat alternatives. The company claims Solein has dramatically lower emissions than conventional protein, and almost completely decouples protein production from land—reducing the need for intensive agriculture.  

German engineering company GEA Group invested €8 million ($9.2 million) in Solar Foods earlier this year, taking a roughly 5.5% stake in the Finnish company and becoming its strategic partner. It is the latest example of GEA’s commitment to sustainability—backing not just the idea of a more sustainable food system, but the technologies that could make it commercially viable.  

“I strongly believe that it is necessary to do something to save this planet,” says GEA Group CEO Stefan Klebert. “We are in climate change—nobody, I think, can ignore this anymore. We can do better.” 

Beyond the Solar Foods investment, GEA is embedding sustainability into its core business. It is currently redesigning the machinery and systems it manufactures—which are used to produce food, drinks and pharmaceuticals—to make them significantly less energy intensive (its technologies are used in dairy processing, food drying, fermentation, freezing, and packaging). The company is targeting net zero across its value chain by 2040, with plans to invest around €175 million ($201.9 million) over that period in decarbonizing its own factories. 

As the debate rages about whether European companies can realistically meet their net-zero targets while achieving the growth needed to remain competitive with China and the U.S., GEA’s stance stands out.  

Earlier this year, a survey of more than 300 European chief sustainability officers by management consultancy Horváth suggested that around two in five companies are reassessing their climate ambitions in the face of short-term performance pressure and geopolitical uncertainty. More than half (57%) of respondents to a survey of European businesses by EY said sustainability initiatives would be among the first to go if they had to make cuts. 

In contrast, GEA Group says it has shown that sustainability can be baked into a profitable business model. Its revenue grew to €2.7 billion ($3.1 billion) in the first half of 2026, 5.7% higher than the same period last year, and its EBITDA before restructuring costs rose 10% to €456.5 million ($526.7 million), with a 16.8% margin.  

Klebert attributes this to a shift in culture: Rather than pursuing incremental productivity gains from an already resource-intensive process, GEA now tasks its engineers with finding step-change reductions in the resources required to produce the same amount. “We put a very strong focus on our engineers to come up with energy saving solutions,” Klebert explains. “I told them, don’t innovate to find 15% more output. We want to do the same thing, but with 30% to 40% less energy, less water, or any other resources.” 

He gives milk drying as an example: GEA developed an industrial heat pump that it combined with a milk spray dryer, allowing one of its customers, the Danish organic milk producer Arla, to produce the same output while cutting total energy consumption by more than half. The energy saving was so dramatic that Arla’s local energy supplier called to check if something was wrong.  

This approach is becoming a growing advantage for GEA Group, as companies across Europe face depleted energy reserves and rising costs this winter, partly resulting from the Iran-U.S. conflict. “A lot of companies are struggling with high energy costs. Especially in Germany, energy prices are sky high and going up because of a lot of stupid decisions that have been made [at a policy level],” says Klebert. “So, for us, the focus on sustainability is not only coming out from the conviction that we need to do something good for the world—it is also a business model.” 

He acknowledges that there are differences between businesses depending on the sector they operate in. “We have an advantage that our customers are highly energy intensive, and if we innovate in saving energy, it helps us to reduce our scope 3 [emissions] and, at the same time, deliver a tangible benefit to our customers,” says Klebert. “There might be other industries where it is different, where the company itself consumes a lot of energy—a chemicals business, for example.” 

However, he believes that business leaders across all industries have a responsibility to drive change. “Of course, we have to stay competitive, but it’s also about innovation, having good ideas and meeting the challenge, because I think there is no other way. Of course, it costs money. But if you have good products, if you are innovative, if you have an efficient organization, you can afford it,” Klebert adds.  

“No company, I’m quite convinced, will go out of the market because of the decision to do something good for the planet. That’s my deep conviction.” 

For the latest coverage and updates from Fortune CEO Forum, as well as insights into the companies on our list, visit this page.

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In 2025, Mark McQuade took a gamble wholly specific to the AI era. 

Arcee AI, the startup he founded in 2023, was focusing on post-training—the process by which an existing model is honed for humans. But McQuade saw an opening: Meta had just backed off its push into open-weight models, a vital (and tricky) middle ground in AI. Open-weight models allow companies (and people) to securely run state-of-the-art AI without turning their data over to, say, OpenAI or Anthropic.

But if McQuade wanted to fill the gap, he and Arcee would have to build their own model completely from scratch, a technical and financial mountain to climb. 

“We saw an opportunity, and we had $30 million in the bank,” said McQuade. “I said ‘let’s do it’ and I bet the company on it. ‘Let’s spend 65% to 70% of our capital.’”

The startup over the coming months burned about $20 million training four open‑weight models, including a 400‑billion‑parameter model called Trinity Large, released in early 2026. $20 million, in AI, is a shockingly low number—conventional wisdom states that you need billions to train a new model, a belief challenged dramatically when China-based DeepSeek surfaced in 2025, with reports that the top-notch model was trained for under $6 million. 

In AI, open-weight models are definitionally geopolitical, and China, so far, has dominated the game. Arcee—whose models have beat Meta’s Llama 3, and have benchmarked on par with Mistral and Chinese models—has been relatively quiet, but is now stepping forward: the startup has raised its Series B at a $1 billion pre-money valuation, Fortune has exclusively learned. The round was led by Vista Equity Partners, Cambium Capital, and Emergence Capital, with participation from Microsoft’s M12, AI10 Ventures, Hitachi, IAG, P7, and Wipro. Arcee declined to disclose the amount raised in this round, but a source familiar with the matter told Fortune it was at least $150 million.

The cash will funnel towards new open-weight models and products, along with growing Arcee’s partnership with the U.S. Department of Energy. (Arcee will also be working extensively with Vista’s portfolio companies.) However, McQuade is very clear: The ultimate goal is to catch China. 

“Everyone talks about China versus the U.S.,” said McQuade (who was previously an early employee at Hugging Face, just acquired by Nvidia for almost $13 billion). “My stance is: just do something great. Catch up to them. Do the work… In order for the U.S. to take the absolute lead in the AI race, you have to be in the lead when it comes to closed and open. The U.S. is far ahead in closed source, but kind of dropped the ball on open source.”

McQuade says it’s time to pick up the ball: “We’re not chasing [Poolside’s] Laguna,” he says. “We’re chasing [Beijing-based Z.ai’s] GLM Flash.”

To get there, efficiency is non-negotiable, McQuade said. And, for Arcee, efficiency’s also the game plan: “We can comfortably say we’re the most efficient lab in the world based on what we’ve done.”

Building in AI is a high-wire act on its own, but the game at the model layer is that much more viscerally competitive, in the U.S. and abroad. McQuade didn’t just pivot, he dove into the deep end, and I asked him: Why cannonball, when you could’ve dipped a toe in?

“Gosh, adrenaline? I don’t know, I like to push the envelope,” he said. “In AI, things change so fast, so what’s the point of dipping your toe in. If you fail, you fail, and at least you tried. If you’re going to do something, go all in.” 

See you tomorrow,

Allie Garfinkle
X: @agarfinks
Email: alexandra.garfinkle@fortune.com

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Good morning. On Fortune’s radar today:

• OpenAI could delay IPO in favor of $1.2 trillion funding round.
• The new Fortune 500 Europe ranking is here!.
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• Expect a rate hike from the Fed today.
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The first instinct of any school meeting a new technology is often to block it. Calculators, phones, YouTube, and now AI. It isn’t necessarily a poor instinct. When you’re responsible for other people’s children, and something arrives that nobody yet understands, a block buys time.

I saw this first hand when I visited Hamilton County, Tennessee; a district that takes STEM seriously, and had invited me out to observe its computer science and maker program. I tried to access ChatGPT on the school wifi, but quickly realized it was blocked. The fix was easy: I simply used the mobile data on my phone to access it instead. Every student in that building would have done the same. This is not a district that’s behind or an outlier. It is doing what the majority of over 13,000 school districts in this country have defaulted to.

It reminded me of a story an English teacher told me, about her efforts to stop her class using AI for homework. While marking her students’ assignments, she noticed about a quarter of the essays she was reading looked remarkably similar. She sent an email: ‘If you used AI, please let me know.’ A hundred per cent of the students responded admitting that they had.  Her policy hadn’t succeeded at anything, other than to show her that children aren’t hiding AI from us. Instead, we are hiding from AI, which is costing us the one conversation that would help them.

I’ve been to school districts across the US over the last three years, and I realized I was seeing repeats of this same story: a blanket block failing to stop the use of a technology that has run rampant, and instead only succeeding in moving it out of sight from the adults who should be supervising it. More than a third of entry-level jobs require AI skills, according to Nace’s 2026 Job Outlook Survey. Ultimately, every district that blocks AI is now making a decision about who gets hired in 2030, and simultaneously pretending it isn’t a decision at all.

AI needs to be built with children in mind

The majority of conversations around AI in education usually focus on whether kids might use AI to cheat in an essay. But the stakes are far higher than that: AI is shaping how we all think, and for children in their formative years, it’s shaping how they learn, socialize, and make decisions. The problem is that almost none of the development driving these systems is treating children’s safety as a priority, nor are they building it in a way that allows kids to learn and use it productively. It would seem, therefore, that we’re running a social experiment on millions of kids without knowing the long-term effect.

The people who study young minds are split. In an NBC survey of the American Psychiatric Association and American Counseling Association, 86% of psychiatrists agreed that AI use among teens would inhibit brain development, replacing human interaction with lower-quality synthetic socialisation. However, 64% agreed that children would learn effectively from AI platforms that tailor lessons in a way that those teaching a class of thirty rarely can. Both can be true, but which outcome we get depends on the tools our children can access, and whether anyone is teaching them to use AI productively. 

The case for restriction might be strong for social media, but it is weak for AI. Feeds hold a child’s attention, but there is no real reason for a child to be fluent in it. Meanwhile, AI packages its harm and skill in the same product. When we impose blocks that are easily surpassed by VPNs or a Wi-Fi switch, we let AI developers off the hook for children’s safety, and schools to step back from the conversation entirely. Out of sight, out of mind. But this isn’t a sustainable plan. 

Schools are struggling to keep up

Today, four out of five students are using AI for schoolwork, according to Stanford’s AI Index. Despite this, only 6% of teachers say their school’s AI policy is clear, and even then, few school districts have worked out a plan for making the transition from a teacher using AI for themselves to using it with thirty or so students. 

When you consider the pace of AI’s acceleration, it’s difficult to point fingers. Within two years of ChatGPT’s release, roughly 40% of US adults had tried it; the PC took twelve years. In the years since AI has been developing, global K-12 edtech funding fell by 82%. Schools were asked to absorb the fastest technology shift in modern history with less support than ever. So, school districts are carrying the liability on their own backs: one superintendent I spoke with recently told me his policy is simple – ‘if it didn’t come from us, it’s on you’. A fairly understandable way to manage risk, but ultimately a terrible way to manage a technology moving so fast, as it leaves the teacher the least resourced to act.

Meanwhile, the gap is widening

Handle it well, and AI could be the greatest equalizer education has ever had. Handle it badly, and we will watch it deepen every single divide we already have. Over 85% of school administrators consider AI education valuable, according to the College Board. Yet, 45% are reporting that access is restricted within their classrooms. The kids who belong to school districts where the only AI policy is no AI will one day be competing for the same entry-level jobs as others who have become literate during their same school years.

During my classroom visits across the country, I see both sides of the coin day-to-day. In some districts, the only AI you see is in an English department’s detection software designed to catch students cheating. In a district right next door, I’ve seen leaders run AI summits for educators, administrators, and AI innovators to learn first-hand how to use and develop frontier technologies so they can best benefit their students. Two districts can be so close in geography and yet headed in completely opposite trajectories. Schools trying to keep AI out of the building think they’re protecting their kids, when in reality, these kids are being left behind.

An example of what can happen when kids are taught to use AI responsibly comes in the form of a 14-year-old boy in Texas. To create greater access to diagnoses in his community, he built an AI app that screens for heart disease in seconds. That’s what’s possible when a child is taught to build with AI instead of just passively consuming it. 

There is no time to waste

Somewhere in a small town in Tennessee, a student is sneaking AI under the desk in a classroom where it’s ‘blocked’. They will use it unsupervised, they’ll try to hide it for fear of getting into trouble, and in the end, all it will have been used for is cutting corners in their assignments. 

In my view, we can make a change before students are put at a disadvantage. We need classrooms to be AI-native and provide access to tools that are safe, so students don’t default back to unregulated tools. For this, we need to redesign AI to emphasize education around critical thinking, complex building and ultimately, protecting human agency. The goal has never been for AI to think for a child, but for the child to think better.

Right now, our schools are not ready, and our teachers are not ready, and there is no plan in place to change that. But this generation doesn’t have the time to wait for them.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

This story was originally featured on Fortune.com

• In today’s CEO Daily: Leaders haven’t forgotten the value of a good boss.
• The big leadership story: The new Fortune 500 Europe is out today.
• The markets: Stocks rebound ahead of the Fed’s rate decision.
• Plus: All the news and watercooler chat from Fortune.

Good morning. I did not expect to return from the Yale CEO Caucus in Washington yesterday feeling more hopeful than when I arrived. After all, this is day 200 of the Iran War, which has killed thousands, exposed security gaps, cost U.S. taxpayers at least $42 billion, and sparked global protests amid rising fuel costs. There’s concern about the economy, the markets, jobs, climate, compute, and the state of the union, not to mention OpenAI’s Sam Altman and Anthropic’s Dario Amodei pondering whether their products will kill us.

Where’s the hope in that? While the semiannual gathering of CEOs, policymakers, journalists and scholars hosted by Professor Jeffrey Sonnenfeld, founder of the Yale Chief Executive Leadership Institute, is off the record, I can share some polling data and feedback from private conversations. Here’s what stuck with me:

A shared desire for common ground and rule of law. I didn’t meet anyone, left or right, who disagreed with the Supreme Court decision to reject President Trump’s plan to make it harder to vote by mail. There were standing ovations for former Vice President Mike Pence, who was honored with the Yale Patriot Public Service Award for Executive Leadership, and former House Speaker Nancy Pelosi, who received the first Yale Patriot Public Service Award for Legislative Leadership. What unites them isn’t their politics but their commitment to the Constitution, public service, integrity and something bigger than themselves. It was a good reminder of the stakes that the nation might face this January if the current administration refuses to recognize the results of the midterm election.

A shared celebration of the importance of human leadership. That’s not always clear from the rhetoric, especially among tech leaders who love to vilify managers as useless layers of bureaucracy in an era of always-on agents, somehow forgetting the value of a good boss. While AI might eliminate redundant roles, it doesn’t diminish the value of a great manager any more than it reduces the value of a great teacher. What drove that home for me was the praise for Corning CEO Wendell Weeks, who was honored with the Yale Legend in Leadership Award. It’s clear from those comments and my podcast conversation with Weeks that the most important factor in making him one of the most transformative leaders in Corning’s 175-year history isn’t his technical prowess but his ability to inspire excellence, loyalty, and respect.

A shift in the conversation around AI. There’s an interest in addressing fears about the technology: 88% of respondents in a flash poll said Trump should address AI safety with Chinese leader Xi Jinping when they meet next week; 74% think he’ll do it. And 93% of attendees disagreed with Trump’s Truth Social post that AI warnings are a hoax. The fears of rogue agents know no boundaries. If the U.S. and China can find some common ground around safety and regulation, we could all be better off.

Contact CEO Daily via Diane Brady at diane.brady@fortune.com

This story was originally featured on Fortune.com

Welcome to this week’s Fortune Gulf Brief. We’ll be covering:  

• Why the Gulf’s startup industry is missing half the picture  
• Geopolitical tensions fail to diminish UAE’s appeal among wealthy expats 
• Abu Dhabi’s Yas Island gets $3.3 billion boost  
• How the UAE is putting billions to work—from German AI to Indian aluminium 
• And, the three we enjoyed reading this week (including the launch of the 2026 Fortune 500 Europe ranking) 

As I reported last week, the Middle East and North Africa region’s gender funding gap remains stark, with male-founded startups accounting for more than 96% of the $375 million in capital that was deployed in August.  

Female-founded startups secured just $8.5 million with a total of two transactions.  

It made for puzzling reading, given that the region’s startup ecosystem, particularly in the Gulf, is thriving, with more women choosing to launch their own businesses. 

Abu Dhabi alone recorded 3,058 new business licenses issued to Emirati women in the first half of 2026, highlighting the growing role of women entrepreneurs in the emirate’s economy.  

So, I decided to dive deeper into the topic to gain clarity on why the disparity persists and spoke to several key players in the ecosystem to help me do so.  

What quickly became apparent was the underrepresentation of women allocating capital.  

“Gulf investor networks are still very male-dominated, especially at decision-making levels,” Lucy Chow, who serves as secretary general in the UAE office of the World Business Angels Investment Forum, told me.  

“That matters—because deal flow follows networks.” 

That’s not to say that progress isn’t being made on the ground.  

In May last year, Aliph Capital, the Gulf’s first women-founded private equity firm, closed its debut fund at $200 million. Aliph Fund I will invest $15 million–$40 million in Gulf-based companies across high-growth sectors, providing capital to drive scale and operational efficiency. 

In recent years, both the UAE and Saudi Arabia have been particularly proactive in making capital more accessible. 

The Women in Tech Accelerator, orchestrated globally by Standard Chartered and executed regionally via partners such as the UAE’s Village Capital and Saudi Arabia’s Falak Holding, has often served as the primary financial lifeline for early-stage female-led tech startups. 

Last week, Standard Chartered and Falak Holding awarded three Saudi women-led start-ups equity-free grant funding totaling $45,000 at Demo Day in Riyadh. 

On 28-29 September, Riyadh will host the Women Shaping Wealth Summit 2026, bringing together an influential community of investors, founders, business leaders, policymakers, and innovators. 

Alongside its main-stage discussions, the summit will host a Live Demo Day connecting female founders with investors, dedicated startup and founder showcases, curated speed networking, mentorship and peer sessions, and structured opportunities for investors, entrepreneurs and leaders to forge meaningful connections. 

You can read my full article here.

Melissa Hancock

As ever, thanks for reading, and do keep in touch with your thoughts and ideas.
melissa.hancock@fortune.com 

This story was originally featured on Fortune.com

The Middle East and North Africa (MENA) region’s startup ecosystem has become increasingly vibrant in recent years and boasts a string of unicorns and innovative businesses.  

But despite the progress that has been made, female founders remain woefully underrepresented in accessing capital.

MENA’s startup ecosystem attracted $1.7 billion in VC funding across 242 rounds in the first half of 2026, according to tech accelerator Wamda. 

However, female-founded startups secured only $2.5 million or 0.14% of this funding total, compared with$1.6 billion raised by male-founded startups across 213 deals.

This funding disparity is far from a one-off.

Aggregate data compiled by Wamda shows that mixed-gender founding teams and female-founded startups accounted for roughly less than 4% of total equity transactions deployed across the GCC between 2019 to 2025. 

This is despite more female entrepreneurs establishing businesses in the region.  

According to a 2025 Global Entrepreneur Survey conducted by GoDaddy, the U.S.-headquartered internet domain registry company, 51% of surveyed small businesses in MENA are owned by women, with 63% of them founded in the past five years. 

Abu Dhabi alone recorded 3,058 new business licenses issued to Emirati women in the first half of 2026, highlighting the growing role of women entrepreneurs in the emirate’s economy. 

It begs the question: if more women across the region are starting companies, why hasn’t their share of the funding pie grown at the same pace?

According to Lucy Chow, a limited partner at U.K.-based VC firm Pact whose investment remit extends to MENA, part of the problem stems from the lack of diversity at the investor level.  

“Gulf investor networks are still very male-dominated, especially at decision-making levels,” Chow, who also works as secretary general in the UAE office of the World Business Angels Investment Forum,” said Chow.

“That matters because deal flow follows networks. I’ve been saying for years that we need more female check writers, but men have to help solve this too, by actively backing deserving female founders.” 

It’s a view that is shared by Basil Moftah, managing partner at Key Capital, a Dubai-based VC secondaries asset manager. 

“Undoubtedly, the VC industry—both regionally and globally—is dominated by male general partners or has a majority of male GPs,” said Moftah. 

“While most people would tell you they’re not biased, surely there is a bias in there. It’s hard to ignore that and the impact it has on funding outcomes.”

Data published by Founders Forum Group, a U.K.-headquartered group of businesses supporting entrepreneurs around the world, shows that VC firms with at least one female partner are 2.3 times more likely to invest in female founders, while VC firms where women make up at least 30% of partners invest 4.7 times more in female-founded companies than all-male firms. 

Female angel investors allocate approximately 35% of their investments to female founders versus 13% for male angels. 

Chow said that female startups still rely heavily on bootstrapping to try to plug the gap. 

“My experience with a lot of female founders is that they bootstrap,” she explained.  

“They are leveraging alternative personal income streams to self-fund. Founders are resourceful and patch together funding, but non-traditional capital won’t replace VC when it comes to scaling.”

She referenced a Mastercard study published last year that showed 56% of women entrepreneurs in the UAE run a side hustle, to achieve financial independence and bankroll early business concepts. 

Some regional industry experts have said that if the trend is to be reversed, Gulf governments need to issue mandates for gender equity in startup funding. 

Chow believes the region needs to build a pipeline of female investors. 

“We absolutely have to treat this as a capital allocation problem, not just a founder problem,” she said. 

“That means more women angels, limited partners, and investment committee seats, but also more female investors in the room, and government measures that encourage capital to flow, not just quotas.” 

The lack of major exits in regional female startups has created a familiar catch-22: investors need success stories to unlock capital, but capital is needed to create those success stories.

According to Chow, the funding imbalance has also led to a heavy reliance on public innovation grants from entities such as Dubai SME and Abu Dhabi’s Khalifa Fund for Enterprise Development to survive bridge periods between equity VC rounds. 

It has also led women to take matters into their own hands, as Sophie Smith, founder and CEO of UAE-based Nabta Health, the first dedicated platform for women’s preventive healthcare in MENA, explained. 

“When we started raising our Seed round in 2021, we set up a special purpose vehicle so that we could accept smaller tickets of $1,000 or more from angel investors,” said Smith. 

“I was looking for female angel investors on publicly available lists and, out of frustration, I set up 2022 Female Angels with a group of friends to identify and publicly list 2,022 female angel investors across the region.” 

Today, the team hosts workshops and bootcamps to upskill and enable women to become angel investors, and manages a list of around 350 active angel investors, with 44 of its 79 angel investors being female. 

Last November, Nabta Health closed a $2 million pre-Series A funding round, bringing its total funding to $4.5 million.

Other initiatives such as Women Spark, founded in Saudi Arabia by Deemah AlYahya, focus heavily on training, mentoring, and facilitating angel investments into female tech innovators. 

While such efforts are encouraging, they are unlikely to move the dial on the scale required for the Gulf’sfemale startup ecosystem to start reaching its full potential.  

“I have been one of those vocal individuals stating that we need governments to step up and to seed funds targeted specifically at female founders,” said Chow.

“Concurrently, wealth funds and family offices can also do their part by allocating a portion, however small, to funding female-led startups.” 

As the GCC presses ahead with pursuing economic diversification, the region can ill afford to leave a growing pool of female entrepreneurs on the sidelines. The challenge is no longer getting more women to start companies—it is ensuring they have a fair shot at the capital needed to scale them.

That will require more than training programs and individual initiatives. Key players across various areas of the economy will need to exercise a more active role in widening the investor pipeline and directing capital toward female-led businesses. 

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Sir Alex Chisolm has been U.K, chair of EDF for more than two years, but he is still awestruck by the power on display when visiting any one of the company’s eight nuclear power stations. 

At Sizewell, which is currently home to Sizewell B, the U.K.’s largest operational nuclear site, he says: “You can stand on the bridge there and feel, wow, this is how we actually make this. This is the room with the magic that’s powering 1.2 million homes, and you’re going to see these giant machines going around amazingly fast. You think, well, that is power.” 

Chisholm stepped down as permanent secretary to the Cabinet Office in 2024 and currently serves as a non-executive director at BT and senior adviser to Boston Consulting Group, in addition to his EDF role. Transitioning from the world of politics and returning to the private sector has been a welcome change of pace. 

“It’s good for people like me who spent probably a bit too much time hanging around Whitehall offices to get out to sites where the real work is done by people to power the nation,” Chisholm says. 

EDF, a French state-owned energy company, sits at 15th on the latest Fortune 500 Europe rankings and recorded profits of €8.4 billion ($9.7 billion) for the 2025 financial year. 

Chisholm first developed an interest in the energy sector while at the Competition and Markets Authority, which was overseeing an energy market review when he was chief executive of the regulator. He also served as head of the business and energy department for four years and says he found the sector “absolutely fascinating.”

“The energy sector is so important to the way people lead their lives, to our business competitiveness, and all the changes happening with the development of AI,” he adds. “So I thought that was a very worthwhile challenge to throw myself into.” 

Rising energy costs ‘put brakes’ on growth

Energy companies and the U.K. government are currently facing pressure to help bring business energy costs down. Gas and electricity costs for businesses have increased by 25% since February, according to industry research firm Cornwall Insight, largely as a result of conflict in the Middle East. 

The Confederation of British Industry has warned that persistently high energy prices threaten the U.K.’s global competitiveness and risk “putting the brakes on the country’s growth ambitions.”

Chisholm believes that the government should be prioritizing reducing energy costs for both businesses and consumers. EDF was among a group of 120 organizations that called for “hidden taxes”, including levies for renewable projects, to be scrapped from energy bills. 

Chisholm says: “The U.K. has a competitiveness deficit now in its energy costs—that is a real call to action. We’re now nearly one and a half times more expensive [than the rest of Europe] for industrial users of electricity, and that is not a position we can continue to tolerate.”

Chisholm regards nuclear power as another key part of the answer. “Nuclear is a very important solution, both for the planet, but also for energy security and supply,” he says.

EDF is currently involved in the construction of two new nuclear facilities in the U.K. Hinkley Point C is majority owned by EDF and it is estimated it will be capable of powering 6 million homes when it comes online in 2031. EDF also owns a 12.5% stake in Sizewell C which is set to become operational in the “mid to late 2030s.” 

The two nuclear plants will be the first to have been built in the U.K. since the 1990s and are a key part of the government’s plan to reduce the country’s reliance on fossil fuels.

The regulatory burden

However, both projects have been beset by delays. Hinkley Point C was originally scheduled to come online by 2025 and had an initial projected cost of £18 billion ($24.26 billion)—this has now doubled. 

Sizewell C also risks falling behind schedule after construction of two key access roads to the site were delayed.

Chisholm believes many of the challenges faced in the construction of EDF’s latest facilities are typical of those faced by large infrastructure projects in the U.K. “Although the plant that we’re building is based on technology called the European pressurized reactor—which was designed for the European market and has already been built in France at Flamanville and in Finland at Olkiluoto—U.K. regulatory bodies here had their own specific requirements,” he says. 

A 55,000-page development consent order (almost 40-times the length of War and Peace) was required to secure planning approval for Hinkley Point C. The public body Natural England also advised EDF to design and install a ‘fish disco’—an underwater acoustic deterrent to prevent marine life from swimming into the cooling pipes that feed the nuclear plant’s turbines. 

“We spent almost a billion pounds on changes to the plant, which relate to reducing the impact on fish,” Chisholm says. “We all love fish but you could have achieved a lot more for fish numbers and welfare at a much lower cost than that.” 

“I understand and respect environmental standards and nuclear safety,” he adds. “The question is, how much is enough?” Chisholm claims that the current regulatory process leads people “unwillingly” to develop rules that “make no sense”. 

The Fingleton Review of nuclear regulations recommended a more balanced approach to environmental protection and was adopted in full earlier this year after John Fingleton, who led the review, said Hinkley Point C had “more fish protection measures than any other power station in the world.”

The proposals aim to speed up the planning process for new nuclear projects by reforming environmental impact assessments but have been criticized by wildlife charities and environmental organizations for representing a false choice between nature protection and development. 

However, Chisholm is a fan of the Fingletonian approach and believes it could have benefits beyond the energy sector and in the wider economy. “If it was easier to get things built in this country, if it was easier to get things done, then we would all be better off,” he says. “It would make Britain the best country in the world to do business.”

For the latest coverage and updates from Fortune CEO Forum, as well as insights into the companies on our list, visit this page.

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Before I co-founded Dexory a decade ago, I had no experience in robotics. I am a go-to-market specialist with degrees in both liberal arts and business, a fiction and fantasy obsessed reader, and I am a woman who comes from a family of doctors. My background isn’t in a lab, on a manufacturing floor or on a campus. I grew up in Romania and after studying in the UK, I spent six years working in marketing, sales, partnerships at Telefonica and Google. 

All these things make me quite unusual in my field, robotics, dominated as it is by super-qualified scientists who tend to be men. In the early days at Dexory, it wasn’t unusual to walk into a robotics meeting and be the only woman in the room.

Don’t get me wrong, things have improved. I see far more women at conferences, in customer meetings, and on our own teams. I see women leading engineering teams, building AI models, designing products, running commercial organizations, and founding startups. We should – and we do – celebrate that, but we shouldn’t mistake this progress for the finishing line. 

I’m biased, but I would argue that physical AI is one of the most exciting industries in the world right now – and robotics in particular. The machines we are building and the tech we are developing will revolutionize the world of work – and could help solve some of the existential challenges we face as humankind, from aging populations to climate change. 

To do that, we are going to need a lot more people. Everyone in robotics knows that one of the biggest challenges of running a company right now is a lack of talent. Robotics founders complain about not being able to find the right people, and then they put out job descriptions that seem designed to attract only those who’ve spent decades in robotics. Nobody grows up dreaming about LiDAR specifications or navigation algorithms; they want to solve meaningful problems. Yet the robotics industry still spends most of its time talking about sensors, autonomy, and hardware instead of the impact those technologies create.

If we want to attract more women – and more exceptional people to the field in general – we need to stop selling “robots” and start selling what they make possible. We need to talk about making dangerous environments safer, about reducing waste across global supply chains, about using AI to solve challenges in the physical world that affect almost every product we use. We must speak the language of problem solving, which we all understand and relate to.

We also need to explain that opportunities in the sector are not just limited to building hardware: because there is a lot more to building a robotics company than the robots.  

As robotics has become an industry rather than predominantly a field of research, companies increasingly need product thinkers, designers, operators, salespeople, industry experts and storytellers alongside brilliant engineers. They need people who understand not only how to make technology work, but how to make customers adopt it and to help businesses scale. They need people with unconventional backgrounds.

Not many people outside of Romania know this, but over the past two years, robotics clubs have been emerging all over the country, with Romanian teams winning international competitions and – most notably – made up of both young men and women. 

That suggests that the next generation of scientists will be more diverse than the last and will provide new opportunities for young people in robotics and other fields. But it also shows just how exciting – and accessible – this tech is to non-specialists. These young people will grow up as evangelists for robotics, and some will take their place in the industry. The US and elsewhere in Europe should do the same, and the private sector can lead the charge by sponsoring these early initiatives and then nurturing young talent over time. 

Not everyone who works in robotics has followed a highly specialized path, and there are many successful robotics companies that have not raised hundreds of millions of dollars, even if these are the companies that you read about in the media or on LinkedIn. 

This isn’t just a problem in robotics – it is a wider issue in venture capital and startup funding: the fact is that big funding rounds tend to get the most attention, and most of those funding rounds go to male founders. 

There is a cultural element too. In my experience, women like to talk about their results and what their teams have achieved and feel like they shouldn’t be talking about themselves until those results and achievements are massive. 

The solution is not only for women to be louder, but for founders to think about the kind of stories they are telling. It is worthwhile to announce milestones, but I would love to see more founders sharing the everyday reality of building a company, including the difficulties, setbacks, and less glamorous parts of the journey.

Talking openly about the journey might make a founder’s career feel more relatable to other women, and seeing the full process might encourage others to think: “I could probably do that as well.” And that helps all of us. 

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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In 2009, the great blogger and cultural critic Mark Fisher picked up on the concept of “capitalist realism,” describing a state of mind where the triumph of this economic organization of life was so complete that it was impossible to imagine an alternative to it. But Fisher, who died in 2017, surely didn’t consider that two capitalisms would compete for headspace.

In one story, the Citrini Research “ghost GDP” thesis, AI is essentially a substitute for labor: codifiable, routine, formalizable work gets automated or compressed, hiring for it dries up, and the firms that move fastest win. In the other, something like Alex Imas’ “relational work” thesis, AI is a complement to labor, raising the value of tacit, contextual, hard-to-codify human judgment, and the firms that treat it as a replacement rather than a force multiplier for people, are quietly mispricing their own workforce.

Gad Levanon, chief economist at the Burning Glass Institute, ran a simple, clarifying experiment this week: ranking every industry’s quits rate against its own 25-year history, rather than against every other industry’s raw rate, splitting the labor market into three tiers that haven’t moved together since 2022—revealing a split between the two capitalisms.

In finance, insurance, information, and professional and business services (FIIPB) the quits rate has fallen to the 13th percentile of its own 25-year range. It sits at 1.8%, down from 2.5% in 2019, a 28% drop, and the lowest reading since 2013. The rest of the private economy is sitting at the 44th percentile, close to its historical norm. Government, education, and health care are at the 71st percentile—effectively unchanged from 2019.

“Job hugging is real, but it’s mostly happening in one part of the economy,” Levanon wrote on LinkedIn. “Only FIIPB has collapsed … because that’s where the jobs stopped.” Levanon found that FIIPB employment peaked in early 2023 and has been falling ever since. “People quit when they have somewhere to go, and in a sector that’s shedding jobs there’s nowhere to go.” Bureau of Labor Statistics data released September 1 shows professional and business services hires fell by 188,000 in July alone, even as job openings ticked up nationally.

When asked what was behind this—was this even the beginning of a reversal of the “financialization” of the American economy over the last four decades—Levanon told Fortune it’s probably not as sweeping as that. More simply, he said it was “a decline in the labor intensity of white-collar work.”

“FIIPB output kept growing; the labor needed to produce it didn’t. Technology, and expectations about what it will soon do, suppressed hiring in codifiable work.” The beginning of this was a “post-ZIRP correction,” he said, a shorthand for zero-interest rate policy, or low interest rates set by the Federal Reserve, but that doesn’t explain a gap that’s “still widening in year four.”

A new working paper out of Stanford’s Digital Economy Lab supplies another missing variable: age. Economists Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen, using high-frequency ADP payroll data covering millions of U.S. workers through June, found no evidence of broad, economywide job displacement, but did find that employment of workers 22 to 25 in AI-exposed occupations now sits 19% below where it would be had it kept pace with their less-exposed peers. Experienced workers in the same occupations show no comparable gap. The divergence isn’t showing up as layoffs—it’s showing up as an absence of hiring.

There’s a matching wrinkle in a Bank of America Institute report published September 9: Gen Z’s rate of switching jobs has overtaken every other generation for the first time since 2021, even as broader hiring slows, and Gen Z is getting the largest pay bump of any generation when it does switch. Read next to Stanford’s finding, that looks like young workers being pushed out of the queue for AI-exposed roles and scrambling laterally into whatever is left, faster than anyone else has to.

Both Levanon and the Stanford team are finding the decline concentrated in occupations where AI usage substitutes for human tasks, while occupations where AI complements workers show flat or rising employment, especially for experienced workers. These are the two capitalisms: substitutable work contracting, complementary work holding or rising, in the same economy, in the same months.

Tyler Cowen has been drawing this distinction for months on his blog, Marginal Revolution, parsing the difference between raw “intelligence” that can be automated, on the one hand, and tacit, contextual expertise, or “Polanyi knowledge,” after the Hungarian-British polymath Michael Polanyi. Stanford’s payroll data finds the substitutable work is disappearing specifically for the workers with the least experience to fall back on—the ones who haven’t yet accumulated the tacit knowledge Cowen’s model says should protect them.

Increasing research is dedicated to the pipeline problem: where does the next generation’s tacit knowledge come from, if the apprenticeship rungs are the first casualties of the proxy war being fought over them? The increasing bans on AI in high schools are part of this equation, as is a recent working paper by “China shock” economist David Autor and colleagues. A three-month randomized control trial of 133 practicing patent lawyers produced, over the long run, advantages “concentrated entirely among senior lawyers,” with junior lawyers showing no average gain. “The largest gains from AI thus accrued to the lawyers who retained the least. Foundational expertise may be a prerequisite for extracting durable skill from AI-assisted practice,” the authors wrote.

The irony is that FIIPB is disproportionately the sector that produces commentary about its own contraction, whether through sell-side research from an investment bank or financial news articles like this one. The people narrating the emergency are closer to its zip code than the rest of the country. The media sector is in something like a moral panic over AI, sometimes about the ethics of AI writing, other times about AI doomsday scenarios, but it’s also got considerable skin in the game. As Semafor’s Reed Albergotti noted, AI safety escaping containment makes for “an incredibly fun story.”

Cowen has been reflective on the issue. Responding this month to mathematicians—UCLA’s “Mozart of Math” Terry Tao among them—who warned that the latest AI breakthroughs are encroaching on their field, he invoked Claude Frédéric Bastiat’s distinction between the seen and the unseen: the visible cost to his own status as an economist, he wrote, is real — “not altogether pleasant for me personally, given how much personal status I have wrapped up in particular modes of economic thought” — but the unseen future gains to the field from AI will likely be “enormous, even if current practitioners cannot foresee most of those benefits today.” He went further than almost anyone else writing about this professionally: “I realize AIs someday will end up as better column and blog writers than I am.”

Given the quits data, does Cowen see something more self-interested in the media’s AI-writing backlash than his own admissions might suggest? His answer resisted the clean split. “I think the backlash is both sincere and self-interested, the two motives are working together,” he told Fortune. After all, he added, many “corporate protectionists” actually think tariffs are a good thing and not “cynical profit-seeking,” but they happen to be wrong.

“People just do not want the world to change so much.”

For this story, Fortune journalists used generative AI as a research tool. An editor verified the accuracy of the information before publishing.

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As more states have begun to introduce wealth taxes, billionaires and other ultrawealthy individuals have been forced to make the hard choice between sucking it up and paying the bill or moving elsewhere. 

Those who have chosen to dodge proposed wealth taxes in states including California and Washington have flocked to Florida. Billionaire Californians face a one-time 5% tax on their net worth, so some, including Google cofounders Larry Page and Sergey Brin and venture capitalist Peter Thiel, left California for Miami. 

Washingtonians who make at least $1 million will also face a flat 9.9% tax starting in 2028, and executives once based there, like Amazon founder Jeff Bezos and former Starbucks CEO Howard Schultz, have also left for Florida. 

Florida has become a safe haven for the ultrawealthy because it has no state income tax, and it’s also solidified itself as an epicenter of luxury and lavishness. Plus, they’re free from the burden of a wealth tax. Three of the primary localities where the ultrawealthy are flocking include Miami, Palm Beach County, and Naples. 

How much are billionaires saving by moving to Florida?

Florida has no state income tax, no capital gains tax, and no wealth tax, but the math on how much billionaires or the ultrawealthy save by living there is a bit more complicated. That’s because the ultrawealthy’s income typically comes from a stock sale or a dividend rather than a salary. Take Larry Ellison, for example. By making an estate in Palm Beach County his primary residence before selling Oracle stock, the billionaire saved an estimated $1 billion in taxes, according to Forbes. 

Wealth taxes hit assets like stocks, real estate, and art rather than income, as MIT Sloan notes.

But the wealth tax is still what garners the most attention. California’s Proposition 40 would slap a one-time 5% levy on the net worth of billionaires who lived in the state after Jan. 1 this year. Fortune’s Marco Quiroz-Gutierrez previously estimated the departures of billionaires like Page and Brin could cost the measure some $29 billion of the $100 billion it’s after. 

So the wealth tax is what encouraged some billionaires to move, but the income and capital-gains taxes they’ll never pay again are what keep them there.

Miami: the billionaire bunker

Miami is where wealth migration is most prominent: 19 of Florida’s 20 richest billionaires officially reside there. Many of them cluster on the same guarded islands like Indian Creek (a.k.a. Billionaire Bunker), where Bezos has assembled a property compound worth more than $230 million. Meta CEO Mark Zuckerberg, Page, and Thiel also live there.

Citadel’s Ken Griffin also moved his hedge fund’s headquarters to the city, and Page has spent more than $180 million building a compound in Coconut Grove. Meanwhile, Miami’s millionaire population has grown 94% in just a decade, to nearly 40,000, according to Henley & Partners’ World’s Wealthiest Cities in 2025 report. 

“It’s one of the best cities in the entire world,” Miami developer Robert Rivani recently told Fortune. “It’s just a great place to live. It’s a great political landscape for people who want to expand, raise families, and that leads to having great real estate growth. All the big guys [are] moving down here.”

Palm Beach County

Palm Beach County has also become a major wealth hub. Larry Ellison made a 16-acre Manalapan estate his primary residence, about 10 miles from Mar-a-Lago. Griffin has also poured about $450 million into a waterfront compound in the county. Meanwhile, Citadel, BlackRock, and Goldman Sachs all have expanded there, earning the area its “Wall Street South” nickname. 

The wealth has piled up fast. Between 2014 and 2024, West Palm Beach and Palm Beach saw their millionaire population jump 112%, which is the fourth-fastest growth of any city in the world, according to Henley & Partners. The Business Development Board of Palm Beach County counts roughly 60 billionaires countywide.

Naples

Naples, long a popular retirement destination, also continues to attract vast amounts of wealth. It attracts what’s seen as passive wealth, or retirees and heirs who prioritize golf, privacy, and beaches. Forbes, which in June called Naples the place “where America’s new ‘old money’ hides,” notes it’s frequently cited as having one of the highest concentrations of millionaires per capita in the country. 

Several billionaires also live in Naples and nearby Marco Island, including Jacksonville Jaguars owner Shahid Khan, who is worth about $13.3 billion. Two of the six priciest neighborhoods in America by price per square foot—Port Royal and Aqualane Shores— also sit in Naples.

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Karin Rådström is used to being the only woman in the room. She was the first to lead Scania’s bus and coach division, having worked her way through the ranks from marketing trainee to head of sales and marketing and executive vice president at the Swedish truck manufacturer.

Now, as CEO of Daimler Truck, she heads up the world’s largest manufacturer of commercial vehicles. Rådström became only the second woman to lead a company in the DAX 40 upon her appointment in 2024 and is one of only 43 women CEOs in the Fortune 500 Europe. “I try to use that as a positive motivation more than a heavy burden,” she says. “The best way to increase the number of leadership opportunities for women is, of course, to be successful.”

Since Rådström became CEO, Daimler Truck’s share price has increased almost 40%, from €33.15 to €46.24, and she has overseen significant growth in the company’s zero-­ emissions vehicle sales, which rose 67% in 2025. But this success has not come easily. Rådström reels off a lengthy list of headwinds: supply-chain challenges, semiconductor shortages, the war in Ukraine, geopolitical issues, and tariffs in the U.S. “It’s been kind of a ride,” she says.

Changing gear

Despite only recently becoming an independent business (formed out of the split of Daimler AG into Mercedes-Benz and Daimler Truck in 2021), Daimler Truck has over a century of history. This year marks 130 years since German engineer Gottlieb Daimler built the very first motorized truck, basing his design on a horse-drawn carriage.

Rådström, a Swede, was surprised by the layers of hierarchy at the German company and the sheer volume of decisions that crossed her desk as CEO. In one of her first meetings, she was asked to look at the designs for a new truck cab and formally approve it. Important decisions were often accompanied by a lengthy slide deck. “Those things don’t work in the changing environment that we have now,” she says.

Rådström has called on the company to operate “simpler, faster, and stronger.” This mantra, which encourages quicker decision-making and greater autonomy, has been central to the cultural transformation that she has spearheaded since becoming CEO. “You never have 100% of the information you’d like,” she says, “so if you don’t decide, you might miss big opportunities.”

Those familiar with Rådström’s leadership style describe her as authentic, strategic, and inclusive. One friend, Charlotte Berg, a consult service director for IT company Kyndryl, first met Rådström at a professional development program run by the Stockholm-based Women for Leaders, and Rådström suggested that they go for a run together. Keeping up with Rådström, a former rower for the Swedish national team, was a challenge, Berg says, but the two became fast friends. To this day, they exchange notes at the end of the workweek on what happened, their feelings, and any lessons learned.

The cultural transformation led by Rådström at Daimler Truck has not gone unnoticed. Klas Bergelind, managing director and industrial tech and mobility analyst at Citi, says Rådström has created a more decentralized organization and has encouraged staff to shed some of its more bureaucratic practices. But there’s still significant work to do, he adds: “Cultural change takes time, and while costs are gradually lowered, other temporary cost headwinds are weighing on results.”

Indeed, despite reporting a 5% uplift in revenue in its Q2 financial results, net profits for the group dropped 48% com- pared with the same period last year. Profitability was primarily impacted by tariffs, but earlier-announced price increases and a more favorable tariff arrangement with the U.S. are expected to boost earnings the rest of the year.

Chinese competition gains ground

Another headwind on the horizon is the challenge from China. For now, the European truck market is relatively secure, but the broader European automotive market is being buffeted by Chinese competition. Sales of Chinese electric cars in the Western European market hit a record high this year, accounting for 14.2% of purchases in the first five months of 2026, according to Schmidt Automotive Research, up from 3% in 2024. Meanwhile, the share of China’s car market that is occupied by foreign brands is in steep decline.

Put simply, Chinese EVs are just better than a lot of the competition, says Howard Yu, a professor of management and innovation at IMD Business School and codirector of the Future Readiness program, which evaluates global car manufacturers. In the Southeast Asian market, the technological superiority of many Chinese-made cars is making European produced vehicles appear outdated, Yu says. “It’s like listening to vinyl in the age of Spotify,” he says. “It’s viewed as cute and nostalgic.”

Daimler

European automakers are well aware of China’s technological advantages and Europe’s higher manufacturing and regulatory costs. In a joint letter to the European Parliament, Volkswagen, Stellantis, and Renault warned of an “unprecedented challenge to their competitiveness.”

So far, the European truck market has largely been insulated from the challenge from China. Chinese companies hold a marginal share of 1.36% in the European commercial-vehicle market, according to market research company Dataforce, and three of the four biggest companies in the industry, Daimler Truck, Volvo, and Traton, are headquartered in Europe.

However, the pressures facing the car industry could be a sign of things to come for the heavy-vehicle sector. Chinese truck companies have been expanding their market presence in Europe. SuperPanther and Sinotruk have both begun production in Austria, while Chinese-backed electric-truck manufacturer Windrose has established a European headquarters in Antwerp, Belgium. As with EVs, Chinese trucks are increasingly technologically advanced, says Thomas Fabian, chief commercial vehicles officer at the European Automobile Manufacturers’ Association. Windrose’s Global E700 truck has a fully loaded range of 700 km, for example, while Daimler Truck’s flagship model has a 500 km range. “They [Chinese companies] are at the doorstep, they’re coming,” Fabian says.

European truck manufacturers have some “moat” in their established relationships and service networks. While cost is an important factor, service reliability and the availability of spare parts are also important considerations for truck carriers, and overhauling an entire fleet is a major investment. But Rådström isn’t relying on that. “It’s on us to work on our competitiveness, stay on top of innovation, and remain strong on cost,” she says.

The European Commission’s requirement of a 40% reduction in emissions from new heavy-duty vehicles by 2030 also risks handing Chinese manufacturers an opening, according to Daniela Costa, Goldman Sachs’ head of European capital goods research. Only 2.4% of trucks operating in the EU in the first quarter of 2026 were zero-emissions vehicles. In contrast, one in four trucks sold in China in 2025 was electric, and the International Energy Agency estimates that China accounted for 90% of the 400,000 electric trucks sold globally last year.

Changes are needed for Europe to remain competitive, including better charging infrastructure, reduced bureaucracy, and faster decision-making, Rådström says: “Our customers run on tight margins, so they don’t have the time to experiment with new technologies. We have to show it can reduce costs.”

In it for the long haul

Defense has also been identified as a key pillar of Daimler Truck’s growth strategy. The company aims to double defense-related revenues to €1 billion ($1.17 billion) by 2028 and has plans to invest “mid-three-digit-million euros” in its newly established Daimler Truck Defence brand. “We have a very strong position because we are industrialized, so we have the opportunity to build a lot of volume, and we can leverage our civil side for defense applications,” Rådström says.

She also hopes that closer partnerships with startups in the military space will lead to innovations that can be translated to civilian vehicles—particularly in autonomous driving. Daimler Truck has ambitions to release Level 4 autonomous trucks—which can handle all driving tasks in most settings without human intervention—to the U.S. market by 2027.

While the involvement of European truck makers in the defense sector is not new, rising geopolitical tensions, increased government defense spending, and the ongoing war between Russia and Ukraine have presented new opportunities in this field. “Unfortunately [defense] is an important industry, which is growing,” she says. Over the past year, Daimler Truck has secured contracts with the German, French, Lithuanian, and Canadian armed forces. “A lot of the time it’s about defending democracy, and that’s not something that makes me sleep badly at night; rather, the opposite,” Rådström adds.

Although defense is one of the fastest-growing areas of Daimler Truck’s business, it is growing from a small base and is likely to remain small. If the company does achieve its €1 billion target, it would still represent only 2% of overall annual revenue.

Securing growth over the longer term will require further innovations as Rådström continues her turnaround program. “It’s about making our customers more satisfied; growing employee engagement, because that’s what makes us successful; and showing that we’re improving in the numbers,” she says.

Rådström remains acutely aware of the ­company’s 130 years of history. “It makes you realize—even if I stay in my role for 10 years— I’m still a pretty small part of the long history of this company,” she says. “So I try to stay humble and will aim to hand over an even better company than what was handed to me two years ago. That would make me really proud.”

For the latest coverage and updates from Fortune CEO Forum, as well as insights into the companies on our list, visit this page.

This article appears in the Fortune 500 Europe special edition with the headline “At the wheel of a 130-year-old giant”

This story was originally featured on Fortune.com

The combined revenues of the companies on the 2026 Fortune 500 Europe list hit a record high of $15.5 trillion this year, equivalent to half of Europe’s GDP.  

The list, now in its fourth year, ranks the continent’s largest companies by revenue. Despite fiercer global competition, geopolitical instability, and technological disruption over the past year, the companies on the list have proven resilient. Profits returned to growth this year, rising 3% to just over $1 trillion, after a 5% decline in 2025.  

Volkswagen holds the top spot for a third consecutive year. Revenue climbed 3.4%, to more than $363 billion, despite Europe’s carmakers being squeezed by global tariffs and growing competition from China. 

European energy companies have also proved resilient despite a tumultuous twelve months, with Shell, Glencore, BP and TotalEnergies occupying the rest of the top five spots. Second-quarter profits at Shell and BP more than doubled as disruption in the Strait of Hormuz pushed oil prices higher. 

Finance remains Europe’s most dominant sector in terms of revenue, profit, and headcount. A total of 105 finance companies feature on the Fortune 500 Europe and together they generated 24% of the list’s total revenue, 40% of its profit, and employ 14% of its workforce. 

Howard Yu, a professor at IMD Business School, credits prominence of Europe’s finance sector to the global reach of its biggest banks and their technical sophistication. “These players have spent decades building footprints across emerging markets and have a depth of presence few global rivals can match. This is a genuine strategic advantage, rather than a legacy accident.” 

HSBC is the most profitable company on the list, with $22bn in profits for 2025. The British lender is one of only 25 companies to generate more than $10 billion in profits.  

Sector revenue breakdown

Despite the combined increases to revenues and profits across the Fortune 500 Europe, margins have narrowed for two years running, falling to 6.5% from a high of 7.1% on the 2024 list.  

This is consistent with the stagflation pressures weighing on much of Europe’s corporate sector, according to Guido Cozzi, professor of macroeconomics at the University of St. Gallen. “The gap between revenue and profit growth suggests that many European companies have been able to pass on only part of the shocks they have faced,” he says. “It’s less a sign that businesses are genuinely booming, and more a sign that prices are rising faster than what companies are actually producing or how efficiently they’re running.”  

The U.K. overtakes Germany 

For the first time in the four-year history of the Fortune 500 Europe, Germany does not have the most companies on the list. The U.K. takes the lead with 76 companies, compared to Germany’s 73. 

Yu attributes this to a more international mindset that has been adopted by U.K. businesses. “After Brexit, they have no choice but to look beyond Europe entirely, with many expanding their presence in the U.S,” he says. “The U.S. is the world’s biggest and most profitable market. It is the toughest gym in the world to train your organization to be lean, mean and competitive.”  

The U.K. also outperforms in terms of innovation. It sits more than 30 percentage points above the EU average on the European Commission’s most recent Innovation Scorecard and is home to more unicorns than any nation except the U.S. and China, according to the Hurun Research Institute. 

Where Europe Fortune 500 companies are based

Together the U.K., France, Germany, and Switzerland are home to more than half of all companies on the list, and accounted for more than 50% of all profits.  

Built to last 

Many of the companies on the Fortune 500 Europe list have long histories. The average company is 109 years old, and more than half have been in business for over a century, surviving global conflicts and adapting through multiple industrial revolutions.  

The oldest company on the list, brewing giant Anheuser-Busch InBev, traces its roots back 660 years to the Den Hoorn brewery in Leuven, Belgium. It ranks No. 65 on the list. At the other end of the spectrum, the youngest company on the list is the German automotive-technology company Aumovio, which was spun off from Continental AG in 2025. 

Taken together, this year’s Fortune 500 Europe list is a story of endurance. Many of the continent’s oldest institutions are still the ones setting the pace, centuries after they were founded. Yet Yu cautions against reading longevity as a strength in its own right: “Many of these institutions have grown too comfortable,” he argues.  

The number of female CEOs at Fortune 500 Europe companies has also shown a marginal improvement, increasing from 41 last year to 43. Total revenues for women-led firms increased by 24% to $1.2 billion and BP is the only company in the top 10 to have a woman CEO, following the replacement of Murray Auchincloss with Meg O’Neill. 

For the latest coverage and updates from Fortune CEO Forum, as well as insights into the companies on our list, visit this page.

This story was originally featured on Fortune.com

FOMO—the fear of missing out—used to be a shorthand favorite of young people worried about not being at the right party on a Saturday night. Now, chief executives are increasingly having FOMO over applied AI. The financial bets are large enough for boards to wince at capital expenditure implications. The outcomes are shrouded in mystery, a particular irritant for leadership teams obsessed with data and clarity.  

Step forward, Aiman Ezzat, the chief executive of technology and consultancy business Capgemini. The French Fortune 500 Europe giant has been in the news after it agreed to sell its U.S. subsidiary, Capgemini Government Solutions, which had been providing tracing and removal data for Immigration and Customs Enforcement (ICE) in America. In line with the great tech selloff over AI spending fears, Capgemini’s share price has been laboring. 

I spoke with Ezzat before the controversy over ICE blew up (Ezzat explained on LinkedIn that the American business acted autonomously to protect U.S. classified information). He told me that business leaders were treading a fine line with AI; there is a sweet spot somewhere between too far, too fast, and stuck on the starting blocks. 

“You don’t want to be too ahead of the learning curve,” he said. “If [you are] you’re investing and building capabilities that nobody wants.” 

“Basically, the need to integrate AI with humans. How do you get humans to trust the agent? The agent can trust the human, but the human doesn’t really trust the agent.” 

Aiman Ezzat

AI is not a big-bang moment; changes will happen in increments. Most leaders can remember the hype around the metaverse—a virtual reality world where we could trade and do business via our dancing avatars (Capgemini itself experimented with a metaverse lab). Mark Zuckerberg was so keen on the idea that he renamed his company after it. Like air fryers, its time may now have passed. 

Agility is the new approach: small tests and pilots before you scale. Capgemini now has labs for 6G mobile technology, quantum computing, and robotics. No one knows which parts of these technologies may be the metaverses of the future. 

“Is everything ready to mature? No,” says Ezzat. “But we want to be there to be able to see when things start to mature, when we can really start scaling up, not waiting to see, ‘Okay, oh, now it’s moving.’ 

“We have to do something, right? So, you have to be investing—but not too much—to be able to be aware of the technology, following at the speed to make sure that we are ready to scale when the adoption starts to accelerate.” 

As I have written before, many large firms are viewing AI primarily as a way to make separate business divisions more efficient. That’s a start, but it is not a “whole enterprise” approach that brings together data and operations from, say, finance and human resources or procurement and supply chains, and then connects them in innovative ways. 

“AI is a business. It is not a technology,” Ezzat says, warning that leaders often fall into seeing AI as a “black box that’s being managed separately. There are technologies behind it, but it’s really about transforming the business. It cannot just be used to keep the house running.

“The question you [the CEO] have to focus on is: ‘How can your business be significantly disrupted by AI?’ Not ‘How is your finance team going to become more efficient?’ I’m sure your CFO will deal with that at the end of the day.” 

Read more: Sam Altman should take Niklas Östberg’s number: What the Delivery Hero founder doesn’t know about going public and shareholders isn’t worth knowing

A well-worn phrase with AI is “human in the loop”—a phrase challenged by one senior technology executive I spoke to recently as being “way off beam.” What we should really be talking about is “human in the lead.” Welcome back, “human-centricity,” a centuries-old social philosophy, formalized as an engineering approach by the 1950s ergonomics movement.  

“How do you deal with what we call AI-human-centricity?” Ezzat says. “Basically, the need to integrate AI with humans. How do you get humans to trust the agent? The agent can trust the human, but the human doesn’t really trust the agent.” 

Ergonomics was about chairs that were built for people, rather than chairs designed to fit efficiently into an office or be simple to stack and move. How to mold AI to work with people is a similar challenge. Bad chairs lead to bad backs. Bad AI is likely to be far more consequential. 

For the latest coverage and updates from Fortune CEO Forum, as well as insights into the companies on our list, visit this page.

A version of this story was originally published on Fortune.com on February 12, 2026.

This story was originally featured on Fortune.com

There once was a time when most cars on the road did not have air bags as a standard under federal law. It took until 1998, in fact, for every vehicle on the round to have an airbag as required by federal law — that’s over 100 years after the invention of the first automobile and roughly 30 years after airbags were first invented as a safety measure. Something like that is playing out again, except this time with robotaxis and cyber protections.

Louay Abdelkader, director of product management at QNX, identified it as a huge problem for the sector, “of course … keep in mind that in automotive safety, it took a while for it to adopt.” Abdelkader told Fortune lawmakers should make cybersecurity a primary consideration akin to airbags, noting that every connected vehicle introduces some degree of cyber risk.

Much of the debate over robotaxis has focused elsewhere, such as whether they are indeed smart enough to avoid collisions, how insurance companies should assign liability in an accident, or how police can deal with driverless cars that commit traffic violations. 

Abdelkader told Fortune lawmakers should make cybersecurity a primary consideration, noting that every connected vehicle introduces some degree of cyber risk.

Robotaxis are proliferating across the country, however, with the robotaxi company Zoox most recently receiving regulatory approval from the National Highway Traffic Safety Administration for a commercial exemption, allowing the paid service broader access without manual controls. Tesla also has moved into the robotaxi space, with the advent of Cybercab in at least seven cities.

Meanwhile, Alphabet-owned Waymo has expanded from its beginnings in Arizona to 11 major U.S. cities—even pairing with rideshare company Uber in a few cities.

Unlike conventional vehicles, robotaxis depend on dozens of interconnected electronic control units, high-speed networking, cloud connectivity, GPS, cameras, lidar, radar and AI models that continuously interpret the world around them. Every one of those components expands what cybersecurity professionals call “attack surface,” or the number of possible entry points hackers can exploit.

While Hollywood often depicts hackers remotely hijacking an entire vehicle, experts say modern attacks are more likely to target the broader ecosystem surrounding autonomous cars. 

Even if attackers cannot directly steer a vehicle, disrupted communications could degrade an autonomous system’s ability to safely navigate. In San Francisco, “tech prankster” Riley Walz organized a group DDOS—a denial-of-service—attack on local Waymos. 

The prank consisted of 50 individuals simultaneously ordering a Waymo on the same dead-end street, creating a pileup that made the company disable rides until the next morning.

The DDOS came despite rules from California, where Waymo operates service in San Francisco and Los Angeles, that require autonomous vehicle manufacturers to demonstrate they can safely monitor, update and maintain their fleets while complying with federal vehicle cybersecurity guidance.

Waymo and the California DMV did not respond to requests for comment.

The advent of generative AI has added to cybersecurity risks in robotaxis. Historically, hackers often needed significant time, technical expertise and resources to identify and exploit vulnerabilities. But AI has dramatically compressed that timeline, according to Abdelkader.

He said malicious actors can use AI to identify vulnerabilities, automate attacks and develop exploits far faster—and with more malicious intent—than Walz’s “prank.”

Abdelkader said cybersecurity for robotaxis is largely the responsibility of both manufacturers and lawmakers. He argued manufacturers must build security into autonomous vehicles from the beginning, not treating it as an add-on.

“When you’re developing a cybersecurity system, you start from the ground up. It’s like building a house,” he said. “If your foundation is not strong, it becomes very difficult for you to build a robust and secure house.”

Like California, some jurisdictions have already begun treating cybersecurity as part of autonomous vehicle regulation rather than an afterthought. Arizona has incorporated cybersecurity planning into broader autonomous vehicle deployment policies, while states including Michigan have established cybersecurity initiatives through partnerships with industry and research institutions.

Internationally, regulators have also moved further. The United Nations’ UN Regulation No. 155 now requires automakers in many markets to maintain certified cybersecurity management systems throughout a vehicle’s lifecycle, while ISO/SAE 21434 establishes engineering standards for cybersecurity across vehicle development.

But in New York City, where Mayor Zohran Mamdani has refused to renew the license for Waymo, cybersecurity has been missing from the debate over robotaxis. The young mayor has instead focused on labor protection, citing taxi drivers as the main point of concern with allowing robotaxis to roam Manhattan.

“If a company like Waymo finds itself in New York City, what they will also find is a City government that is committed to delivering for the workers who keep the city running,” he said at a press conference. “Those workers also include our taxi drivers who, for far too long, have been sold a dream of being able to work their way to the middle class.”

Mamdani’s office did not respond to a request for comment.

But Abdelkader argues that all lawmakers across the country should build on existing frameworks rather than waiting for a cyber incident to expose a weakness. He says policymakers often separate safety from cybersecurity too often, even though “they are tied at the hip.”

“The legislators and politicians have to work with them to make sure that moving forward, if there are improvements that need to be done, what type of support is required,” he told Fortune. “You need to be able to talk and share that feedback. That’s the only way for the industry to grow effectively and benefit society.”

This story was originally featured on Fortune.com

Hello and welcome to Eye on AI. In this edition:

• AI’s X-risk breaks into the mainstream
• Anthropic CEO Dario Amodei calls for a coordinated industry safety effort
• Anthropic details attempts to misuse its AI models
• China’s top spy warns AI could pose a risk to the Communist Party
• OpenAI is violating California’s new AI safety law, watch dog group says.
• Half of companies aren’t following their own AI governance policies, E&Y survey says.

In the past few days, I’ve heard a lot of people repeating that old saw—often wrongly attributed to Vladimir Lenin—about there being “weeks when decades happen.” It certainly seemed to be one of those weeks in AI. Concern about existential risk has been a strain of AI discourse for decades. But, despite occasionally making headlines when someone like Elon Musk, Sam Altman, or Geoffrey Hinton would express their fears about AI posing a grave risk to the species, it never really cemented itself in the general public’s consciousness in the way, say, climate change, or the risk of nuclear war, has. If politicians debated AI regulation at all, the discussions centered around data center construction and utility bills, jobs, education, mental health, algorithmic discrimination, and civil liberties, not the risk of rogue AI killing people—maybe even all the people. Until now, that is.

The drumbeat of dire warnings from employees resigning from—or in some cases still working for—Anthropic, OpenAI, and Google DeepMind, all saying that the leading AI companies are developing the technology recklessly and risking human extinction has dominated the global news cycle for an entire week (which is really saying something in this day and age.) AI company CEOs and politicians have been stirred to respond. After years in which both domestic AI regulation and efforts at some kind of international AI governance regime had mostly stalled, suddenly the air is electric with possibility.

My Fortune colleague Nick Lichtenberg had a good story on why the resignation jeremiad of former Anthropic and OpenAI safety researcher Jacob Coxon had such impact when previous warnings, often from much higher-profile individuals, did not. The short answer is that coverage of the Hugging Face incident and other “rogue AI” episodes as well as people’s own experiences using AI agents seems to have opened the Overton window on discussing “loss of control” dangers. The timing, with Anthropic on the verge of an IPO and OpenAI edging closer to one too, also no doubt played a role.

The question now is what happens next? Fortune editor-in-chief Alyson Shontell sat down with Altman on Friday to ask him those questions for her “Fortune 500: Titans & Disruptors of Industry” vodcast (we just call it “Titans” for short.) Altman said the company was in favor of coordinating an industry-wide slowdown in the pace of AI development with bitter rivals, including Anthropic CEO Dario Amodei and SpaceX CEO Elon Musk—two men with whom he has had acrimonious and, in the case of Musk, litigious disputes—as well as Google DeepMind, Meta, and perhaps others. He hinted that such discussions were already underway and that a coordinated slowdown might be announced soon. He also said that, if necessary, he would have no problem telling investors that OpenAI had taken actions to prioritize safety that had cost them financially—and that OpenAI’s investors were warned of this possibility going in. He also definitively said OpenAI would not go public this year, in part due to the current concerns about the safety of the latest AI models, but also, he hinted, because OpenAI’s business isn’t yet in the right place. You can check out the full vodcast episode here. It’s well worth your time to watch.

A coordinated slowdown?

After Alyson’s interview, Amodei put out a blog post also calling for a coordinated slowdown or pause among frontier labs in democratic countries. He said that in some cases, though, coordinating with other AI labs would require an antitrust exemption from the government. He also said that Anthropic would appoint independent evaluators to be permanently on-site at its offices to review its safety work. (He mentioned the nonprofit AI evaluation company METR as his preferred partner for this.) He also said that the U.S. and other democracies should try to strike some kind of international AI governance agreement with China and authoritarian states, if possible. Altman quickly came out and endorsed most of what Amodei said—in particular saying that OpenAI would also embed outside evaluators alongside its research teams—although he was careful to note that “pacing does not mean stopping.”

In the wake of Coxon’s warnings and Amodei’s call to action, a number of U.S. lawmakers introduced legislation or renewed efforts to push forward existing bills. Some, such as a bill introduced by Vermont independent Sen. Bernie Sanders, call for an outright ban on the development of “artificial superintelligence” and mandate that U.S. AI companies pause current research until safety techniques improve. Others, such as a bipartisan bill from Republican Sen. Ted Cruz, Senate Majority Leader John Thune, and Democratic Sen. Amy Klobuchar, would impose a duty on AI companies to prevent catastrophic harms. There were also calls for Congressional oversight hearings on AI’s catastrophic risks. Former President Barack Obama urged Democrats to put AI governance at the center of their legislative and campaign agenda. Meanwhile, a group of 70 U.K. parliamentarians signed an open letter calling for the British government to ban the creation of artificial superintelligence and work on an international AI treaty.

Trump pushes back

But there was strong pushback from some of the politicians that matter the most. President Trump posted to his Truth Social platform that the only guardrails AI needed “is a STRONG AND SMART (High IQ!) PRESIDENT, and the U.S.A. has that in spades!” He criticized Amodei by name, criticizing him for “pretending to be a ‘perfect little angel’” and said his administration had already stopped Anthropic from “doing bad, or potentially bad, ‘things.’” He said the U.S. already had regulatory power and criminal laws that applied to AI companies and that there was “a SICK conspiracy going on against AI and Data Centers, and the only one that is happy about it is China.” He made similar comments in a phone call to Nvidia CEO Jensen Huang that Huang, with Trump’s permission, broadcast to a live audience at an “All in Podcast” summit. This was followed up by the Republican Speaker of the House, Rep. Mike Johnson, saying that fear of AI was drummed up by the media and that “we’re not going to take stupid, knee-jerk reaction prescriptions on this.” Not to be outdone, Chinese state media also criticized Amodei’s proposals, saying they were “self-serving” and “Cold War tactics” designed to hobble China’s technological and economic rise.

With all of that, it seems the prospects for some kind of executive order mandating improved AI safety are poor. The same goes for any actual legislation, such as a bipartisan bill from Republican Sen. Ted Cruz, Senate Majority Leader John Thune, and Democratic Sen. Amy Klobuchar, that would impose a duty on AI companies to prevent catastrophic harms—at least until after the November midterms. Three points though that have come up in the discussion that are worth addressing.

Are antitrust concerns legit?

One is the debate about whether AI companies need an antitrust waiver to talk to one another about slowing development. Some, such as former Trump administration AI and crypto czar David Sacks, have said the AI companies don’t need such a waiver to coordinate a slowdown. And I agree that we should not grant a broad waiver to these tech giants. But I do think that there are legitimate concerns from the AI companies that any discussion of a pause—or of a coordinated decision not to undertake certain product innovations—could create antitrust issues.

Currently, each new generation of AI models tends to drive down the cost of existing, older models. So limiting the rollout of newer models would potentially keep prices higher for longer for consumers, which would seem to open the AI firms up to antitrust claims. (Matt Levine at Bloomberg had a good column on this.) Also, some of the specific innovations that worry AI safety experts, such as greater use of looped Transformers, also happen to have the benefit of using fewer tokens than forcing a model to spit out its complete reasoning trace in its “chain of thought.” This too has the effect of potentially lowering costs for consumers. So prohibiting this technique on safety grounds would also tend to result in higher prices for customers. Again, that looks problematic from an antitrust perspective. For what it’s worth, Chris Lehane, OpenAI’s chief global affairs officer, has come out and said OpenAI doesn’t think it needs an antitrust waiver to discuss shared safety standards with the other AI companies. He also said that there have already been discussions with Anthropic and Google DeepMind on safety standards. But the issue may be that these standards are voluntary, with no mechanism to compel compliance if one company cheats on its commitments. Enforcing the standards would presumably require government action.

Is product liability law enough?

In an example of the strange bedfellows this issue has created, Sacks and former Biden administration FTC head Lina Khan have both said that existing product liability laws could be used to prevent AI companies from releasing unsafe products. Sacks in particular has said that these laws are the reason no new government agency is needed to police AI companies. But there are two problems here. One is that product liability laws generally only apply to products that are sold to customers. Some of the biggest concerns with AI risks lately—as was the case in the Hugging Face incident—have involved unreleased, internal models that were undergoing development or were only deployed inside the AI companies themselves. Product liability law would not cover these internal models.

What’s more, while the fear of liability lawsuits might deter unsafe behavior by AI companies, it might not—and if it doesn’t, suing the companies after the fact is not ideal. This is especially true if the risks are actually existential ones, such as engineering a bioweapon. Suing won’t help us if we’re dead. But even if the risks are merely bad—like hacking into a single financial institution or hospital, manipulating the stock market, or taking out an electrical grid—suing a company after the fact won’t really provide the outcome society wants. Better to prevent these things from happening in the first place. That’s why we do have agencies that police systemically important financial institutions, regulate air travel, ensure power that grids adhere to certain standards, etc.

What about ‘regulatory capture?’

Finally, Sacks and others, including some on the more libertarian left as well as some of the CEOs of AI companies that are slightly behind the frontier, have attacked the proposal for a coordinated pause and agreement on safety standards as an attempt at “regulatory capture.” The claim is that these companies will write the rules in such a way that their leadership position at the front of the AI race gets locked in. I am not denying that this could happen. But it also seems that there are ways to prevent this from happening. Accelerationists like Sacks act as if all regulation results in regulatory capture. But, as I mentioned in a previous newsletter, UC Berkeley AI researcher Stuart Russell likes to quip that there are more mandatory requirements for sandwich shops in San Francisco than there are on OpenAI or Anthropic. And you don’t see too many restaurateurs complaining about regulatory capture. It is simply not the case that mandatory safety rules always result in regulatory capture.

I would also argue that a certain degree of regulatory friction that happens to privilege incumbent players is a price worth paying for a safe industry in cases where failure poses significant risks to human life or physical and financial health. In fact, the industries that pose the greatest potential risks of mass casualty events tend to have fewer players in them, and yes, the burden of regulatory compliance is one of the reasons. But I think this is a tradeoff the public actually thinks is worth the fact that it may also mean they pay slightly more for certain things. There are only a handful of companies around the world that design and build nuclear power plants, for example; only a handful that make commercial aircraft, too. But these also happen to be some of the safest industries out there in terms of their actual operational records. Would there be more players in these industries if there were fewer government safety rules and inspection regimes? Almost certainly. But is the public screaming about regulatory capture and asking for safety standards on nuclear power plants and aircraft to be relaxed? 

With that, here’s more AI news.

Jeremy Kahn
jeremy.kahn@fortune.com
@jeremyakahn

Before we get to the news, just a reminder to check out this week’s episode of our new vodcast Fortune AI Weekly. This week, Bea Nolan and I talk to Substack cofounder and CEO Chris Best about his decision to add an AI writing detection feature to the platform. We also talk about AI doomerism going mainstream and the controversy over OpenAI’s Navier-Stokes mathematical breakthrough. You can check out the vod here on YouTube.

Also, come join me at the Fortune AIQ Summit at the New York Stock Exchange on October 1! We’ll join C-suite leaders Bank of America, Booking Holdings, Citi, Ecolab, Elevance Health, United Healthcare, S&P Global, and more to hear about how they are using AI to deliver the growth, innovation, and transformation that is putting them at the top of their respective industries. It promises to be an afternoon of eye-opening insights and inspiration. You can register to attend here. 

This story was originally featured on Fortune.com

Former Palantir engineer-turned New York state Assemblymember Alex Bores knows Americans want AI regulation. He co-authored the RAISE Act, New York’s frontier AI safety law. He ran this year for Rep. Jerry Nadler’s open congressional seat on that platform, even as many of his donors came from within the AI industry. But that didn’t stop Leading the Future, a super PAC funded in part by OpenAI president Greg Brockman and Andreessen Horowitz, from spending more than $7.6 million against him over that law. Public First Action, with $20 million from Anthropic, spent on the race in Bores’ corner. Total outside money in the race topped $40 million, the most expensive House primary of the cycle. Bores still lost.

That loss helped lead to Who Decides, the nonprofit Bores launched on Tuesday with his former chief of staff, Anna Myers. So far, it has raised $10 million and aims to raise $20 million more in 2027, for a $30 million total ahead of 2028. Bores intends the nonprofit to unite the AI advocacy organizations Democrats already trust, help them build out their own agendas rather than hand them one, and establish “a shared floor of an agenda on things that we all want to see good done.”

“Give the American people a say in how AI develops,” Bores told Fortune. “Most voters have an answer key in their head for every question that they ask” on issues like Medicare or the Green New Deal. But with AI, Bores said, even the messaging lives in this gray area. “We’re in this limited time where it’s not even just the answers that are up for grabs, but even the questions that are being asked are up for grabs.”

The RAISE Act, which New York Gov. Kathy Hochul passed into law late last year following a tenuous time in Albany, necessitated a coalition of 55 organizations, filled with different stakeholders from AI policy to chatbots in school. That wasn’t the case for those against the act. “The opposition was always the same. It was a small subset of Silicon Valley that thinks there should be no regulation on AI whatsoever.”

That’s part of what drove Bores to create Who Decides. The group isn’t trying to outspend Leading the Future or Build American AI—Bores said he wishes he had the resources. Instead, it’s targeting 11 battleground states through organizations already active there. Outreach accelerated after Jacob Coxon’s resignation from Anthropic last week. “The seven major presidential candidates since my election, the 16 Congress members since last week,” Bores said of Coxon’s resignation. So far everyone who’s reached out has been a Democrat, though Bores said he’s open ears for anyone, regardless of political ideology.

Weak laws and weaker willpower

A recent Gallup poll found the majority of Americans, 56% to 58%, want stricter gun laws, while measures like background checks has close to 90% support in both parties, per Pew. And despite this finding, which has coexisted for decades, Congress rarely acts, something usually blamed on lobbying outspending a diffuse majority. AI seems to follow the same trajectory.

“The basics of this issue, while the urgency has changed a lot in the past week, the basics have not, which is that 80% of Americans want there to be more regulation on AI, and that’s across parties,” he said. Independent polling this year puts the figure somewhat lower but still in the same direction: a February–March 2026 Annenberg Public Policy Center survey found 65% of Americans say the government has done “too little” to regulate AI, including majorities of Democrats (77%), independents (72%), and Republicans (53%).

Public sentiment gets grayer when you look at one of the most prominent faces within the AI industry. In May 2023, OpenAI’s Sam Altman asked to be regulated when he testified before the Senate Judiciary Committee. But by May 2025, he reversed course, telling the Senate Commerce Committee that requiring government approval would be “disastrous.” Anthropic’s Dario Amodei held the pro-regulation position throughout, even as Anthropic-linked money flowed into the same political fights.

Regardless of what stances people have at first and ultimately land on, Bores said while industry figures keep landing on the same conclusion, a narrower set of financiers spend to stop it. “So many of the mega donors who are pushing for there to be no regulation whatsoever are Republican mega donors,” he said, naming Marc Andreessen and Elon Musk.

One can argue that’s what happened to his RAISE Act—what passed was a watered version that didn’t survive that same money intact: third-party audits and whistleblower protections were stripped before it passed. But still, that hasn’t changed Bores’ view of it: “The RAISE Act was, arguably still is, the strongest AI safety bill in the country,” he said, though he expects Illinois and Massachusetts to surpass it soon.

Avoid the circular firing squad

In 2025, Sen. Ted Cruz inserted language into the “One Big Beautiful Bill” that would have barred every state from enforcing any AI law for 10 years. Seventeen Republican governors asked for it to be stripped, before the Senate voted 99–1 to remove it.

Cruz is now co-sponsoring a new federal AI safety bill with Sen. Amy Klobuchar and Majority Leader John Thune, built around safety testing and incident reporting. It may be D.C.’s most likely AI bill to pass yet, but if you read between the lines, it’s essentially Cruz’s old bill wrapped in federal packaging (and it comes with the very real possibility of removing all state AI bills with it). “Spot on,” he told Fortune about that reading. “It’s people trying to use this momentum and this crisis to shut down the real power people have to regulate.”

Despite the external politics playing on Capitol Hill, Bores also acknowledged the Democratic party has a less than stellar track record on getting messaging right. Often it’s because advocates who agree keep splitting the difference into separate fights. “Democrats are very passionate about making a difference, and that passion is usually well placed,” he said, “but that occasionally gets misdirected into turning into a circular firing squad and saying, no, my sub-issue is more important than your sub-issue.”

His case? “The people who are opposing almost every issue in AI are the same people… we should be sitting at the same table.”

This story was originally featured on Fortune.com

If you’ve ever wanted to get your MBA—this is a great week to get started on the journey, in part thanks to the release of Fortune’s latest ranking of the best MBA programs for 2025. 

The highly competitive ranking process saw that many of the top schools retain their clout—with Harvard Business School, University of Chicago (Booth), and Northwestern University (Kellogg) landing the coveted top three spots, respectively.

But there’s much more to meet the eye than the initial data shows. Each program is unique, and for many students, any ranking is just part of the decision-making process to figure out where is best for their own education and career goals.

Fortune used nearly a dozen different data points to gauge 98 MBA programs across the country. For context, these are the averages among all the programs:

What makes the best MBA programs the best?

Holistically-speaking, the best MBA program prepares students for the business world of today and tomorrow through a modern lens. Students become the best at problem solving, critical thinking, and making data-driven decisions. Having an industry-experienced faculty and a constantly-evolving curriculum are paramount.

Looking more quantitatively, the best programs are highly sought after, and thus students enter with competitive application materials, including multiple years of professional work experience, decent undergraduate GPA, and high GMAT or GRE scores. Because of the growing costs of higher education, Fortune also weighs high tuition negatively. Once in the program, exceptional retention and graduation rates are key. Finally, after graduation, success is indicated by the ability to land jobs with high-paying salaries.

The M7 schools often check all of these boxes. Take Northwestern University (Kellogg), for example. Entrants had median GMAT scores of 740 and average undergraduate GPAs of 3.7. Retention and graduation rates are both above 99%. Three months post-grad, about 92% of students seeking a job were able to land one—with median salaries of $175,000.

Fortune also heavily factors unique data from our lists of the biggest companies in the country.

This in part has helped some programs soar in the ranking. Washington University in St. Louis (Olin) is a glaring example. The school’s MBA program is the alma mater to 19 Fortune 1000 CEOs and CFOs.

“I’m proud of the momentum here at Olin and honestly not surprised that an outsized share of our students make it to the C-Suite. At Olin, we’re a tight-knit, hyper-connected community: We have the unique ability to provide a truly individualized educational experience,” Mike Mazzeo, dean of the Olin Business School, tells Fortune.

The school’s faculty, alumni network, and regional business community contribute heavily to students’ success at Olin, he adds.

“Students choose Olin because they know our approach makes them ready on day 1 and poised for career 6,” Mazzeo says.

WashU experienced the biggest jump of any school this year, rising 18 spots to No. 21.

Sleeper MBA programs with stories to tell

Experts will remind candidates to not forget to look at programs that typically fall outside of the top of the top in the rankings since they often have very similar statistics in terms of outcomes, but may be slightly less competitive and expensive.

Take, for example, the University of Texas–Austin (McCombs). Fortune deemed them to be the No. 12 best MBA program (an increase of five positions from last year). The cost of tuition per year is about $60,000—which is nearly $20,000 cheaper than many of the top 20 programs. And guess what, their students have almost identical job land rate and salary outcomes as the M7.

Georgia Tech (Scheller), the No. 19 best MBA program, has a similar story to tell. Graduates typically see median annual salaries of $165,000, and the tuition is just $42,790 per year. Plus, the school does not require students to submit GMAT/GRE scores to apply.

One of the universities that may be an even greater bang-for-your buck—as long as you are willing to live in Utah—is Brigham Young University. The school was ranked No. 37 for 2025, but the tuition per year for students is only about $15,500. That’s significant especially considering graduates leave the program with about $120,000 in median base salary.

The 5 cheapest MBA programs

The 5 easiest top MBA programs to get into

If you’re looking to go to a top MBA program, but are worried about getting accepted, then the percentage of applicants receiving an offer is likely top of your mind. Among the top 25 programs, the University of Washington (Foster) has the highest acceptance rate.

How does the ranking actually work?

We will be the first to say that the rankings world is not perfect. Each year, schools will be happy if they rose, and frustrated if they declined. However, we hope to just provide applicants a glimpse into how schools compare to each other with metrics we feel best measure success.

Fortune’s ranking is based on an opt-in process, meaning only schools that respond to Fortune’s invitation and submit a response to our data questionnaire have the ability to be included. This is done in order to judge programs with the most consistent and across-the-board data metrics. While many schools release data about their applicants and graduates, specifics often differ from school to school. 

Fortune reached out to more than 200 schools this year, and close to 100 chose to participate. Some schools that typically appear on Fortune’s rankings, such as Georgetown University and Babson College, decided to not participate this time. We hope to see them back next year.

There were also several new-comers to our list this year, including University of Georgia (Terry), San Jose University State University (Lucas), and Troy University (Sorrell). 

With a revised methodology as well as different schools, there is bound for ranking change. The biggest ranking risers were:

• Washington University in St. Louis (Olin): No. 21 (+18)
• University of Tennessee-Knoxville (Haslam): No. 36 (+16)
• Southern Methodist University (Cox): No. 30 (+13)
• University of Massachusetts–Amherst (Isenberg): No. 41 (+13)

The biggest decreases were:

• Indiana State University (Scott): No. 60 (-35)
• University of San Diego (Knauss): No. 87 (-29)
• CUNY Bernard M. Baruch College (Zicklin): No. 76 (-29)
• University of Denver (Daniels): No. 83 (-28)

However, ultimately, while ranking can be important, it is not an end-all-be-all assessment of one school. It should merely present prospective candidates a general idea of the level of prestige one school may be on par with—and where they might take their career.

Harvard Business School declined to comment for this piece.

Check out all of Fortune’s rankings of degree programs, and learn more about specific career paths.

This story was originally featured on Fortune.com

In March, shortly after the Supreme Court struck down President Donald Trump’s International Emergency Economic Powers Act (IEEPA) tariffs and paved the way for $100 billion in import taxes being redistributed back to American importers, U.S. Trade Representative Jamieson Greer shared his idea of what these companies should do with this influx of cash.

“If I were these companies, and somehow they get this windfall, the most important thing and the smartest thing they should do is give it as bonuses to their workers,” Greer told CNBC.

It appears some companies have heeded Greer’s suggestion. As businesses receive more than $100 billion the U.S. Treasury has doled out in refunds since May, many are vowing to lower prices or pay down debts. A handful, however, are giving the cash back to their employees. 

In its second quarter earnings report last month, houseware brand Williams Sonoma said it would allocate $10 million for one-time payments to 401(k) accounts to eligible employees  “in recognition of their efforts navigating the IEEPA tariffs.”

“We’re so appreciative to have the money back and to be able to reward our employees with part of it,” President and CEO Laura Alber said on an earnings call. “They have done such an amazing job.”

TJX, which received $331 million total in tariff refunds, will similarly put a portion of its aggregated refunds into paying employees extra.

“Due to these tariff refunds, the company accrued incremental expenses of $112 million for year-end incentive compensation and discretionary bonuses for eligible associates globally,” a spokesperson told Fortune in a statement.

American companies and consumers alike have kept a close eye on the tariff refund process, particularly after Federal Reserve research showed they were the ones shouldering the brunt of the tariff costs. While companies like Walmart and FedEx have promised to compensate consumers for tariff-related inflation through lower prices or direct rebates, the unconventional decision to hand employees cash from tariff refunds indicates just what a pervasive impact the import taxes had on U.S. companies.

“Companies have a lot of different margins for how they adjust to tariffs,” Alex Durante, senior economist at the Tax Foundation, told Fortune. “They could pass all of it along to consumers, they could also reduce investment, they could reduce hiring, they could cut back on certain employer perks and forms of compensation, if they wish. And I think that this is just perhaps another way of thinking about that.”

How U.S. employees have been impacted by tariffs

Greer’s rationale for giving workers a portion of the tariff refunds goes back to one of Trump’s initial motivations for implementing levies in the first place: to bring back manufacturing jobs to the U.S.

“The whole reason the president imposed these tariffs was to try to reshore, affect our massive imbalance in trade that we’ve experienced over many years because of China, Vietnam, the EU and others,” Greer said. “If the companies are going to get this windfall, they should pass it along to their workers as a bonus or a raise, because that’s the purpose of the program.”

It appears the tariffs had the opposite effect in reshoring, with manufacturing jobs in the U.S. actually shrinking by more than 100,000 during the first year of Trump’s second term. Laura Ullrich, director of economic research at the Indeed Hiring Lab, previously told Fortune tariffs and the uncertainty surrounding maintaining supply chains, could be a reason for this dip.

“Oftentimes when there is heightened uncertainty, it’s just difficult for businesses and people to make decisions in real time,” she said. “And so that slows down employment. It slows down all those processes.”

In addition to hiring constraints, tariffs may have also suppressed wage growth, according to Pantheon Macroeconomics analysts Samuel Tombs and Oliver Allen, who argued companies slashed raises in order to maintain or take back margins when the IEEPA tariffs were in place. It’s one reason why companies may feel compelled to give workers back some cash from the duties, the Tax Foundation’s Durante suggested.

Instead of lowering prices or offering refunds to consumers amid ongoing tariff uncertainty, “what are some better ways we can retain our employees and incentivize them to want to stay with us or to want to want to work for us?” he said.

Tariffs, after all, have likely had an impact on workers’ retirement plans, at least indirectly. Though markets have recovered from Trump’s previous threats to impose sweeping import taxes, economists have found evidence tariffs will have longer-term reductions in stock prices, from about 7.33% to 10.13% across indices within the next couple of years. Lower stock prices means fewer returns for employees with retirement money in the markets.

“It is the case, absolutely, that tariffs do impact capital, and thus the equity markets,” Durante said.

This story was originally featured on Fortune.com

When Fidji Simo announced she was leaving her role as one of the most senior members of OpenAI’s leadership team after a seven-year battle with her chronic illness, Postural Orthostatic Tachycardia Syndrome, or POTS, the news felt unexpectedly personal. My little cousin has POTS, and it’s been devastating to witness. Simo’s post said she would be focusing on how to use AI to cure these types of diseases, but I wondered if it was just another tech executive making lofty promises about AI that may never materialize.

“Do people like my cousin have any reason to have hope that AI can actually make a difference for their health?” I asked Simo when I reached out to her after the announcement. I also told her how much I admired her courage to be so open about her condition. That’s not easy for a highly scrutinized public figure. Simo was previously at Meta for a decade, where she oversaw the Facebook app, and then served as CEO of Instacart, which she brought public in 2023, before joining OpenAI in 2025. 

“Yes,” she answered. “I created a company, ChronicleBio, to tackle just that.” 

We hopped on the phone to chat about it in Simo’s first interview since leaving her position as OpenAI’s CEO of AGI deployment, where she reported directly to CEO Sam Altman. While now her main focus is her recovery and a never-ending schedule of medical appointments, she’s also working on growing ChronicleBio as well as continuing to advise OpenAI. She’s still in a Slack channel with the company’s leadership team, where she regularly speaks with Altman, and Greg Brockman, the OpenAI cofounder and president who took over the bulk of Simo’s responsibilities when she departed. 

Brockman’s wife, Anna, has POTS in addition to two other chronic diseases. ChronicleBio’s three cofounders—Simo, Rohit Gupta, and Rishi Reddy—also either have chronic diseases themselves, or have a family member with one. These days, Simo says she’s “physically the worst I’ve ever been.” There is no cure for POTS. It causes dizziness upon standing up, fatigue, brain fog, headaches, and other symptoms, owing to an imbalance in the body’s autonomic nervous system.

Chronic conditions are “becoming a real epidemic,” Simo tells me. “We’re talking about hundreds of billions in lost productivity, and so there’s very big potential in finding drugs for these conditions.” 

In its first year as a company, ChronicleBio has performed 890 blood draws from 709 patients in Utah, Arizona, Texas, and India. It has over 3,500 tubes of blood in its “biobank,” the company tells me. It’s extracted 153 terabytes of data from the blood—that’s three times the 45 terabytes GPT-3.5, a 2022 model from OpenAI, was trained on. The company has raised $15 million to date. 

The next big thing: home blood draws. On Aug. 11, ChronicleBio will launch a sign-up link for mobile phlebotomy trucks to come to the homes of people with certain chronic diseases. Participants will get an in-depth report on their condition, free for the first 250 people. In exchange, they’ll give their biological data to ChronicleBio.

The goal is to learn more about diseases and improve the success of clinical drug trials, something Simo says would be nearly impossible without AI.

The transcript below has been edited for length and clarity.

Courtesy of ChronicleBio

In preparation for this interview, you sent me an article that you said encapsulates ChronicleBio’s approach. It talks about how some patients with long COVID were participating in a clinical trial. The drug was working well for them, but then the trial was canceled for supposedly being ineffective for the group as a whole. 

Fidji Simo: Yes, so that’s really what ChronicleBio is meant to solve. We have seen a lot of clinical trials fail because the pharmaceutical companies aren’t able to identify which subset of patients [a drug] could work for. So they end up giving the drug to everyone with the same diagnosis. Let’s say it’s POTS. But there could actually be five sub-diseases within POTS, and the drug would work for one of them, but not the other four. So the clinical trial fails when it could have succeeded if we could have identified these people upfront. It seems really simple, but it hasn’t been done for these conditions.

So what your company is doing is finding patients with similar symptoms, grouping them together, and then testing drugs on those subgroups so the trial is more likely to be successful?

That’s exactly right. We have already found five sub-diseases where the biology is really different, despite the symptoms being the same. And now that we understand the biology, we can map that to existing drugs that would solve the problem, and so we’re going to start testing these existing drugs on our patient population before the end of the year. Then we would partner with biotech and pharma to develop new drugs, with the goal of having suitable therapeutics for every part of this patient population.

What exactly do you mean by a sub-disease?

The sub-diseases don’t even have names right now. That’s the problem. So, the way the medical system names these syndromes is by their symptoms. In the case of POTS, it’s called Postural Orthostatic Tachycardia Syndrome. It’s basically named after the symptom: Tachycardia means your heart rate goes up when you stand. But for one group of patients the disease might be driven by the immune system. For another, it’s driven by the mitochondria. The underlying biology is very different, and that’s why one drug isn’t going to work across everyone even if the symptoms are the same.

Very cool. Backing up for a second, is it an amazing feeling to have gone through such a long medical journey yourself, and now you’re in a position of power to actually improve the system?

Yeah, you know, it’s obviously a horrible disease, and I certainly wish I could have dodged it. But at the same time, I think it has given me enormous meaning. The delta between the disability from these diseases and the amount of funding and research being done on them is terrible. If you look at a condition like chronic fatigue syndrome, it is considered the most disabling disease of all diseases. Like, when you look at the disease chart, it’s completely at the bottom, worse than cancer. 

And yet, if you look at the amount of funding for this condition, it’s absolutely pathetic for two reasons: One, it primarily affects women, so of course you get less funding. Second, while it completely disables you, it usually doesn’t kill you. And so the combination of these two things has made it that these diseases are really ignored, even though they affect people at the prime of their lives. You usually get affected between 20 and 40 [years old], and you’re completely disabled. You’re taken out of your life entirely, and so it’s a crazy amount of suffering.

I have a lot of empathy for people with chronic fatigue and chronic conditions after being pregnant. It kind of feels like that. [Earlier in our conversation, Simo mentioned she was bedridden for five months of her pregnancy, and she developed POTS a few years later.]

Yeah, imagine that 24/7, impossible to move. [Some] patients are fully bedridden in the dark, sensitive to light, sensitive to sound. It’s a really terrible quality of life, and to me, it seems impossible that with the tools we have today, we would continue to conclude that diseases are incurable and that patients should be in a dark room for years. We owe them something better, given the progress that we’re seeing in a lot of disciplines.

So what’s different now with AI? What does it unlock that wouldn’t have been possible before? 

The complexity of these diseases made it that without AI they were incredibly difficult to solve. Like I said, they’re multisystem, so you need to be looking at the state of the nervous system, the state of the immune system, and how it correlates with your genetics. All of that is a massive data problem that was very hard to get your hands around without AI. And so finally we have AI, and then on top of that, you have the cost of these analyses going down. Doing a genetic analysis years ago was way more costly than it is now. Analyzing 150 terabytes of data would have been either impossible or would have taken years, and now it takes us minutes. 

So that’s what gives me a lot of hope. I’m physically the worst I’ve ever been, but at the same time, we are at a moment in time where we have the best tools we’ve ever had to solve diseases that are considered incurable.

What AI models are you using?

We’re using a combo of OpenAI and Anthropic models. We’re using anything that’s available that can help.

Why do you need to collect blood to get the right data?

The reason I did ChronicleBio is because I really think that we are missing true biological data to make progress towards discovering drugs. Right now, a lot of the models use a lot of EHR data—medical records. But medical records don’t tell you enough about biology. They’re incredibly noisy. They don’t tell you how the human body works. If you look at LLMs, they work so well because the internet existed, right? You already had all of this language. We are missing the internet of biology. 

What’s the latest initiative you’re working on?

Right now we’ve acquired all of this data [from blood] by partnering with clinics, but we think it’s really important to get that data from anyone who wants to participate. We’re now in the process of opening up our tests to anyone in the U.S., with mobile phlebotomy coming to their house. That’s going to allow us to have a much larger dataset, but also reach patients that are bedridden, that are in the sickest stages of the disease. And we actually return the data to patients, so that gives them more information about that condition in case that can help direct them towards a particular therapy. So that’s basically what we’re up to.

That’s amazing. When does it start?

It’s next week [on Aug. 11]. We partnered with mobile phlebotomy companies that collect the blood in a kit. They send that to us. We get it analyzed. It takes a couple weeks because these analyses are very robust. And then we send back a report to the patient about everything we learned, and that data goes into our database. And then over time, if we have more findings about which sub-disease the patient might have or things like that, we continue keeping them posted, and then they can take the test over time, so at multiple points in time, so that we can also see how they evolve. So if they went on a particular drug, did their immune system change? That gives us longitudinal data about the evolution and progression of these diseases.

There are already a variety of mail-in blood tests out there. How is what you’re doing different? 

That’s right. The test we do is very focused on these particular complex chronic conditions. So it’s not just the standard blood tests that are common. It’s a really advanced research-grade blood test.

How much will it cost?

We’re making it free for the first 250 patients because we really want to make sure they are getting value out of the report. After that, it’s going to cost $400. We’re doing it at cost, meaning that’s what it costs us, and we’re charging the same for patients. The whole point for us is not to make money. It’s to collect data so we can find cures.

This is all so fascinating. I’m glad we did this.

Thank you for your interest! We’re excited. You know, when I was at OpenAI, I said, “I think if AI accomplishes everything but doesn’t cure disease, that would be a very sad state of affairs.” The real promise of AI has always been to cure disease. I think it would be a tragedy if we had all of these amazing tools in our hands, but weren’t able to turn them into drugs that can save patients’ lives on a time frame that matters. 

This story was originally featured on Fortune.com

CADDi, a startup that sells AI software to help manufacturers organize and use their engineering and production data, has raised $114 million in a new funding round that values the company at $1.2 billion.

Eight new and existing investors took part in the investment, which is the company’s Series D funding round, the Tokyo- and Chicago-based company said.

Among them are Moore Strategic Ventures, Coreline Ventures, Toyota’s growth-stage fund Woven Capital, and HR Tech Fund, the corporate venture arm of Japan’s Recruit Holdings. One new investor was not identified. Existing backers Atomico, Globis Capital Partners, and the JPS Growth funds, managed by a Japan Post Bank subsidiary, also took part in the funding.

The valuation is more than double the $470 million CADDi reported in March 2025. The new round brings CADDi’s total funding to $234 million, the company said.

Founded in 2017, CADDi’s initial product, called CADDi Drawer, was designed to address a common problem in manufacturing firms: they buy too many similar parts from different suppliers. The AI-powered product ingested technical drawings and then searched a customer’s own databases for similar or identical parts the customer had previously purchased or already has in inventory. The software also provided information on the defect rate of those parts, allowing the customer to decide if they wished to use existing stock, repurchase the item from an existing supplier, or try a new supplier.

In the past two years, the company has broadened its product suite, creating what it calls an “AI data platform for manufacturing.” The platform can integrate different data types from across multiple systems that customers use—from CAD files to enterprise resource planning software to HR systems—and structure it for use by both people and AI agents. CADDi Drawer has been renamed CADDi Explorer and is now joined by CADDi Agent, an AI agent designed to help manufacturing companies make decisions about standardizing parts and perform quality impact assessments, which analyze how a given design change will impact performance and safety.

CADDi has also launched six “workflow” products aimed at specific tasks, designed in part to capture the tacit knowledge of experienced engineers and workers. For instance, CADDi Design Review flags potential errors in new drawings and CAD models based on past problems with similar parts.

Yushiro Kato, CADDi’s cofounder and CEO, tells Fortune that CADDi uses its own proprietary AI model to analyze product data like drawings and CAD files, and general-purpose large language models for documents and spreadsheets. “I’ve never seen anybody who uses LLMs to do design reviews because it doesn’t understand drawings or CAD,” he said.

More than 80% of the knowledge about manufacturing work processes, and often why a company chose a particular supplier or designed a part in a particular way, is never recorded anywhere, Kato said. Instead, it exists in the heads of experienced employees. CADDi’s AI platform is designed to capture and codify that knowledge.

Kato declined to disclose revenue or customer numbers, but said sales are more than doubling year over year and that the company now has customers in 22 countries, although the U.S. is a core focus. In Japan, he said, more than half of the country’s 100 largest manufacturers use CADDi. Meanwhile, CADDi’s headcount has grown to about 900 staffers, up from 600 in early 2025. 

He said the money from CADDi’s latest fundraise will go toward expanding its product lineup, building AI models that understand manufacturing-specific data such as 3D CAD files and 2D drawings, global expansion centered on North America, and hiring.

CADDi tends to market its products based on measurable returns to its customers, such as lower direct material costs or shorter engineering lead times—critical, he said, for automakers and other manufacturing firms competing with Chinese rivals.

The biggest obstacle to adoption, Kato said, is change management. Getting workers to alter how they have traditionally done things takes hands-on help, which is why CADDi employs more than 100 customer success staff, outnumbering its salespeople. Like many AI companies, it’s started hiring “forward deployed engineers” to help customers use AI effectively. “The goal is to change the organization and create a business impact,” Kato said.

Kato frames CADDi’s ambitions around what he calls “the physical bottleneck.” AI capabilities are compounding, he said, yet little in the physical world has changed since ChatGPT debuted. Today, AI can build a e-commerce marketplace website in hours. Developing a new car, by contrast, still takes about four years from planning to delivery. “Even if AI makes thinking ten thousand times faster and produces ten thousand times the theory, the upside from AI gets diluted in the physical world if it still takes four years to mass-produce cars,” Kato wrote in a recent essay on CADDi’s website.

CADDi’s stated goal is to accelerate physical innovation tenfold by 2035—which, for a car, would mean four to five months from planning to delivery. Automakers typically go through about 20 design review cycles for a single product, Kato said, often because problems surface only at the prototype stage. CADDi wants to run more of those steps in parallel and catch problems earlier by pooling the know-how of veteran engineers into what Kato described as a kind of “superhuman” veteran.

This story was originally featured on Fortune.com

Eugene V. Debs never lived to see ChatGPT, but the socialist labor leader who fought for shorter working hours would probably recognize Bernie Sanders’ latest pitch: If AI is coming for workers anyway, it should help them spend less of their lives at work, not just make billionaires richer.

Last week, Sanders and California Rep. Mark Takano reintroduced the Thirty-Two Hour Workweek Act, which would lower the standard workweek for nonexempt employees from 40 to 32 hours, thereby pushing employers to shorten schedules or pay overtime for the difference. Sanders, who has advocated for responsible AI use and, more recently, pushed for a pause on AI development, has pointed to the positive benefits he sees stemming from the technology: an ease on American labor.

“At a time when artificial intelligence and robotics will radically transform our economy, it is imperative that the financial gains from this new technology benefit working families, not just a handful of billionaires and corporate CEOs,” Sanders said in an announcement of the bill.

The bill, initially introduced by Takano in 2021, still won’t guarantee every American a three-day weekend. Instead, starting at least six months after enactment, it would gradually lower the overtime threshold for covered workers until it reaches 32 hours following four years of becoming law. Employers could still schedule longer weeks, but would owe overtime—and they can’t cut affected workers’ weekly compensation or benefits because of the change. 

Takano similarly argued that labor law has failed to keep pace with nearly nine decades of technological change. “Since then, cell phones, the internet, and now AI have increased worker productivity,” he said. “Work has fundamentally changed. It’s time that labor standards caught up.”

The bill would also establish overtime after eight hours in one day and double pay after 12. Under current federal law, covered nonexempt employees generally receive time-and-a-half only after working more than 40 hours in a week, with no federal requirement for daily overtime.

The proposal arrives amid a corporate race to use generative AI to produce more work with fewer people. A 2026 analysis by Boston College sociologist Juliet Schor for the University of Massachusetts Amherst’s Political Economy Research Institute estimated that AI-led productivity gains could allow 35 million U.S. workers—28% of the workforce—to move to a 32-hour week within a decade. Like Takano, Sanders has also called for this in the past. He introduced a Senate version of the bill in 2024 and argued that reducing work hours was the next chapter in the labor struggle stretching back more than a century. 

A century-old fight over workers’ time 

Debs was one of the country’s biggest proponents of the shortened workday. In his 1890 essay “Eight-Hour Day A Righteous Demand,” Debs called shorter hours a matter of basic dignity. “By making eight hours a lawful day’s work, no man, woman, nor child is wronged,” he wrote.

Debs and other labor leaders pushed for shorter work hours when many Americans still worked 12-hour shifts six or seven days a week. (To be sure, Debs pushed for the standard eight-hour day, in a time when Americans worked six days a week). In 1926, Ford Motor Company became one of the first major U.S. employers to establish a five-day, 40-hour week for factory workers. Congress eventually cemented the 40-hour standard through the Fair Labor Standards Act, signed in 1938, which set an initial 44-hour week before phasing it down to 40 hours by 1940.

Nearly nine decades later, Sanders argues that the standard has outlived the economy that it was built on. Since 1979, net productivity has climbed roughly 90% while typical workers’ hourly pay has risen about 33%, according to Economic Policy Institute data—a gap advocates for shorter workweeks cite as part of the broader case for reform. 

There is also evidence that reducing hours can benefit workers without damaging their perceived performance. In a six-country study coauthored by Boston College sociologists Wen Fan and Schor and conducted with the advocacy group 4 Day Week Global, nearly 2,900 workers across 141 companies cut their schedules by about five hours a week. After six months, they reported less burnout and better physical and mental health, job satisfaction, and work ability. For Sanders, the question is whether those efficiencies will result in layoffs and larger corporate profits—or allow employees to reclaim some of their time.

Still, moving from voluntary company trials to a federal labor standard would be a much larger test. During a 2024 hearing held specifically to consider Sanders’ earlier 32-hour-workweek bill, Louisiana Sen. Bill Cassidy argued that the added labor costs could raise prices and threaten businesses operating on thin margins. Cassidy now chairs the Senate’s Health, Education, Labor, and Pensions (HELP) Committee, which would consider a Senate version of the legislation.

“A 32-hour workweek is not a radical idea,” Sanders said. “It’s time to reduce the stress level in our country.”

This story was originally featured on Fortune.com

This holiday season, a new obsession is sweeping through American homes: the “Ralph Lauren Christmas.” But it’s not just luxury shoppers and Manhattan brownstones getting swept up in visions of tartan, velvet, and brass candlesticks. Instead, millions of budget-minded Americans are piecing together their own versions of ‘90s holiday opulence, raiding their local dollar stores and thrift shops to capture just a hint of Ralph Lauren’s famed festive glamour.​

On TikTok and Instagram, the phrase “Ralph Lauren Christmas” has surged by over 600% compared with last year, while Etsy searches for related decor are up more than 180%, and Google Trends shows the phrase soaring to unprecedented heights. “This search trajectory suggests the trend has moved beyond niche interest into mainstream holiday planning behavior,” said Chase Varga, director of marketing at ListenFirst, a marketing analysis firm founded in 2012.

Scrolling social feeds reveals a relentless parade of fireplace mantels draped in plaid and velvet, clusters of vintage nutcrackers beneath dark-wood shelves, and tablescapes positively roaring with holiday maximalism. Much of the aesthetic is rooted in nostalgia for the 1990s—a time when American opulence and the heirloom “good Christmas” felt accessible and aspirational at the same time.

​Opulence, on a shoestring

Yet what’s striking about the trend’s viral run is not a rush on luxury home retailers, but the sheer number of creators frank about finding “the look” at thrift stores, chain discounters, or dollar stores. Faux brass candlesticks, plastic nutcrackers, and off-brand plaid blankets are hauled out as budget stand-ins for the designer’s signature style. Where original pieces can easily cost hundreds, the challenge—and the thrill—is achieving the aura of a Ralph Lauren Christmas at a fraction of the price.​

This isn’t just driven by aesthetic longing—it’s economic necessity. Inflation and rising costs have pounded the holiday budgets of most Americans, with many stretching their dollars further and starting their holiday planning earlier. Retailers themselves are leaning into the trend: Even premium guides to replicating the “heritage” style pair aspirational items with affordable alternatives from mass-market stores.​

Consumers chase traditional cues—tartan throws, velvet ribbons, gold baubles—sourced wherever they can be found. Social media groups and YouTube channels brim with tips for “dupes” and convincing DIYs that evoke the comfort and warmth of the Ralph Lauren look, minus the price tag. For many, assembling these elements isn’t aspirational irony but an earnest desire to conjure the cozy, elegant holidays they remember from childhood or Hollywood movies.​

Nostalgia, or something more?

Some critics online question whether this “trend” repackages basic Christmas traditions under a new label. Yet for others—especially millennials and Gen Z creators who grew up yearning for catalog holidays—“Ralph Lauren Christmas” describes a mood as much as a collection of objects: a longing for warmth, security, and family gatherings in uncertain times.​

The style’s core motifs—a roaring fire, deep jewel tones, layers of texture—evoke not just designer luxury, but memories of grandparents’ houses and TV holiday specials. In a jittery economy, the comfort found in ritual, tradition, and a whiff of elegance conjuring “old money” (another breakout search term) feels especially magnetic.

No matter where it’s sourced, the Ralph Lauren Christmas is less about brand names and more about atmosphere. The Ralph Lauren Christmas of 2025 owes as much to nostalgia and the ingenuity of ordinary Americans as it does to Madison Avenue—proof that with enough fairy lights, brass-look candlesticks, and dollar-store tartan ribbon, anyone can conjure up a bit of ‘90s opulent holiday magic.

​For this story, Fortune used generative AI to help with an initial draft. An editor verified the accuracy of the information before publishing. 

This story was originally featured on Fortune.com

Prepare your “working hard or hardly working?” quippy response: Companies want you to role-play as an employee before they finalize your offer letter.

Work trials aren’t brand new, especially in more technical fields, but companies are increasingly leaning on them to find qualified candidates in a job market flooded with AI-optimized résumés and cover letters:

• It could be an unpaid mock task you complete off-site that mirrors what you’d do on the job.
• On the other end of the spectrum, the work trial might be a week in the office with the team you could potentially join. If the work you complete on trial benefits the company, the candidate generally has to be paid for it.
• About two-thirds of companies use some form of skill-based hiring for entry-level roles, according to a 2025 survey conducted by the National Association of Colleges and Employers.

In theory, a trial is great for checking a candidate’s skills and collaboration style while weeding out folks who are just really good at interviewing. But they can be a barrier to employed workers who can’t afford to take a full week off work for a long test that might not end in a job offer. And they can quickly turn exploitative when they’re unpaid.

Applying for a job feels like screaming into the void. Companies have spent the last few years downsizing after pandemic-era overhiring. With AI supercharging the hiring process from both sides, an in-person element could make finding a job more human…if a candidate can make it past the bots to get to that round.—MM

This report was originally published by Morning Brew.

This story was originally featured on Fortune.com

Elena Rybakina won the U.S. Open women’s singles tournament last week, defeating reigning champion Aryna Sabalenka in the final face-off. Now, the 27-year-old is ranked the number one female player in the world. But just 10 years ago, the Moscow-born Gen Zer was at a crossroads: go to college, or stay focused on her career as a tennis player. Even defying her father’s wishes for her to stay in education. 

“I finished school and I had to decide if I should go to college,” the U.S. Open champion told the Women’s Tennis Association in 2020. 

“My dad wanted me to go to college because he was worried. He saw the results, but it was difficult for us financially. It’s not easy. Like every parent, he was worried if I got injured.” Plus, her father reasoned that she could get a “better education” abroad. 

“I had offers to universities in America, but I didn’t even think about it because I wanted to keep playing. I had like 15 offers. My dad really wanted me to go.” 

Ultimately, Rybakina chose the uncertainty of professional tennis over the security of a college education—and that decision set her on a path that would eventually make her a three-time Grand Slam champion, scoring 14 singles titles across 10 countries. “Because of tennis, I could get a better education,” she added.

Changing her citizenship and becoming a world champion, earning $11.4 million

Once Rybakina had made the decision to skip college and continue her tennis career, she made another pivotal choice that would shape her professional journey. The athlete had been playing for Russia up until that point, but in 2018 she switched federations to Kazakhstan—and even changed her citizenship. The Central Asian country offered the then-19-year-old funding and support to grow her career. 

Rybakina has made major strides in her decade-long career as a tennis pro. For years, she worked her way up through the ITF Circuit and WTA qualifying. In 2019, she ended the year ranked No. 36 for her first Top 100 finish and winning her maiden WTA title at Bucharest. 

Just one year into training with a private coach, she began turning that steady progress into a breakthrough run on the WTA Tour; she broke through in 2020, playing in five tour finals, more than any other player that year. Rybakina later snagged her first major title at the 2022 Wimbledon Championships, and in 2023, reached the 2023 Australian Open final.

From there, Rybakina’s career—and her earning power—continued to accelerate. 

Rybakina capped off last year by winning the 2025 WTA Finals undefeated, earning $5.235 million for her victory—which was the largest prize-money payout in the history of women’s sport at the time. By now she had several titles under her belt as well as a slew of brand sponsorships, including the likes of Nike, Adidas, and Red Bull.

And 2026 has been Rybakina’s best year yet. 

Earlier this year, she clinched her major title, winning the Australian Open. And just one week ago, following her in the U.S. Open Grand Slam victory, the Gen Zer took over Sabalenka’s No. 1 ranking, which the Belarusian held on to for nearly two full years. 

Today, Rybakina is the 10th highest-paid tennis star in the world, according to Forbes, earning $11.4 million on the court and $6 million off-court. And by winning the U.S. Open women’s singles, Rybakina brought home another $5.5 million in prize money.

“Honestly, I didn’t expect [anything] like this coming from this tournament,” Rybakina said after her recent New York City tournament win. “I’ve been dealing a little bit with injury, but somehow everything aligned on my side…I was coming here for the last 10 years, and it was never successful. Nothing close to that, and it’s just incredible.”

Later this year, the 27-year-old is also slated to compete in the WTA Finals to reclaim her championship title. After a season that has already delivered two Grand Slam titles, a record-setting payday, and the world No. 1 ranking, Rybakina is on a tear in the tennis world. 

If she didn’t forgo the chance to go to college in the U.S., it’s uncertain if she would have lived the same whirlwind success.

This story was originally featured on Fortune.com

Miami hasn’t always been a destination for luxury and wealth. For a long time, it was seen as a fun place to party and vacation—an escape from the world. But as more wealth has moved from major cities like New York and Los Angeles, Miami has become an epicenter for luxury and lavishness. 

In 2025, a home in the city sold for more than $100 million for the first time ever. Jeff Bezos has assembled more than $230 million in property on Indian Creek Island, the guarded enclave known as the “Billionaire Bunker,” and Citadel CEO Ken Griffin moved his company’s headquarters there. Mark Zuckerberg, Larry Page, and Peter Thiel all also bought property there. 

And now, 19 of Florida’s 20 richest billionaires officially reside in Miami-Dade County, according to data published earlier this year. The pull is familiar: no state income tax, plenty of year-round sun, and a business-friendly climate that COVID-era remote work only improved. Meanwhile, Miami’s millionaire population has grown 75% in a decade, at least in part because of heat from California’s Proposition 40, a proposed one-time 5% wealth tax on billionaires that has some Californians moving coasts.

So now that the wealthy have their luxury homes in Miami, a developer is betting they need somewhere lavish to work, too.

Not your average cubicle

Betting against what many saw as a cratering office market, Robert Rivani squarely believes the office isn’t dead. He just thinks it’s boring. 

“When everyone thinks it’s falling apart,” he told Fortune, “that’s when we’re jumping in.”

So his answer is a $100 million redevelopment at 1691 Michigan Ave., steps from Lincoln Road—the world-famous promenade in the heart of Miami Beach—that he’s branded as “Class X.” Rivani, a Beverly Hills-born developer who built his real estate career buying up shopping centers after the 2008 crash and later pivoted into Miami hospitality, has made a habit of moving into asset classes just as others write them off.

The 163,000-square-foot building, which was formerly called The Lincoln, was bought for $62.5 million in 2024. The Rockwell Group gutted and redesigned it into something more like a five-star hotel than a stale space for answering emails.

Photo courtesy Rivani

The amenity deck is the heart of the development, which includes a Monarch Athletic Club performance center with a cold plunge and sauna, its first location outside of California. A stem cell clinic and a longevity doctor administer peptides, and a members-only speakeasy is private for tenants by day and public after hours. The development also includes an omakase restaurant, a concierge, a hospitality director, and a valet.

“Our valet is supposed to be this shock-and-awe, Vegas-style valet,” Rivani said. “You have a twinkle-light ceiling. As soon as you hit the pavement, it follows your car all the way through in the valet with 150 feet of linear waterfall.”

Plenty of landlords have tried luring tenants back with on-site gym memberships and free snacks. But Rivani calls those gestures gimmicky—and instead has invested in having a gym, doctor, wellness suite, and happy hour all under one roof. Rivani, who said he has dealt with autoimmune issues, built the wellness focus inspired by his own needs.

“The [two things] money can’t buy are time and health,” Rivani said. “And that’s where the concept came together. I said: ‘Okay, we’re not doing office. We are defining what office should look, feel, act like.’ And that’s where the brand and the whole concept came about.”

Photo courtesy Rivani

“And I wasn’t scared because I thought it was a whole different genre,” he added. 

Class X has moved well beyond concept and has landed several big-name tenants. Playboy is relocating its global headquarters from Los Angeles to a 20,000-square-foot penthouse at the building on a 10-year lease. Shark Tank star Daymond John has also signed on, as did Morgan Stanley, Wix, Raymond James, Comcast, and Coldwell, as well as a roster of longevity and medical practices. 

Rivani said the building was roughly 90% pre-leased before opening, with rents approaching $175 per square foot, a figure he calls “pretty much unheard of.” 

A second phase is already planned atop the parking garage, adding a restaurant, more office space, and rooftop padel courts. Beyond that, Rivani wants to take Class X national with members using amenities across cities like an office version of a Soho House. He’s targeting a fundraise in 2027, once the concept is proven.

“We’ve not raised a penny to date,” he said. “I’ve bootstrapped this entire thing myself.”

This story was originally featured on Fortune.com

Humanoid robots took center stage at the World Humanoid Robot Games in Beijing last August, winning over audiences by attempting—not always successfully—athletic feats like sprinting, weightlifting, and kickboxing. Yet one of China’s leading robot startup founders thinks there are still a few years before robots truly break into the public consciousness. 

“As models keep maturing, [embodied AI] will reach GPT-3.5,” said Yao Maoqing, co-founder of the Chinese robotics firm AGIBOT, during the Fortune Leaders Forum in Macau on Sept. 8. “People differ somewhat on timing, but overall it’s within the 3-to-5-year window.” 

Yao’s use of “GPT-3.5” was a reference to the model underinning ChatGPT; OpenAI’s chatbot was the first time an AI service could perform common, everyday tasks—and not just specialized ones—with a success rate between 80% and 90%.

AGIBOT is part of a wave of Chinese startups developing humanoid and quadruped robots. With 9,700 units shipped during the first six months of the year, AGIBOT is the top seller of humanoid robots, according to data from Counterpoint Research released in late August. The startup is considering an IPO in Hong Kong.

While robot dance performances and boxing matches get headlines, manufacturers are frantically searching for real-world applications for their tech. Shanghai-headquartered Keenon Robotics, for instance, has rolled out robots aimed at automating hotel services.

Wan Bin, Keenon’s chief operating officer, noted that one international hotel is using eight robots to greet guests, deliver room service, clean rooms, and manage the restaurant floor. “This scene is one that will become increasingly common in the future.”

Other robot manufacturers hope to apply their products in more industrial settings. “We’ve invested very heavily in developing robots for the industrial sector,” said Jianxin Pang, UBTech’s vice president and vice dean of research. “But first, we’re starting with relatively common scenarios with a big enough market—that helps us ensure return on our investment.” 

Yet many humanoid companies acknowledge that building robots for industry is no simple task.

“It’s genuinely difficult for today’s humanoid firms to develop a robot that can run stably inside a factory,” Yao acknowledged. “Industry players are brutally honest: They care about four metrics—success rate, cycle time, stability and cost—rather than what technology is used. From that standpoint, we absolutely have to train our robots to 100% efficacy first.”

In late June, AGIBOT ran a six-day livestream that demonstrated that its robots hit a 99.99% success rate completing over 64,000 manufacturing tasks. Reaching that milestone required eight-hour sessions in the middle of the night for a month, Yao said on-stage. 

Still, Yao was optimistic that embodied AI would follow the same scaling law that transformed large language models. 

“Most industry teams believe that embodied AI will follow the exponential scaling law we discovered in digital intelligence and large language models,” Yao said. “As data volume rises and your model’s parameter count grows, there will definitely be a step-up in intelligence.”

Correction, Sept. 15, 2026: An earlier version of this article misstated details about Keenon Robotics’s work in hotels.

This story was originally featured on Fortune.com

As of 9 a.m. Eastern Time today, oil is trading at $106.57 per barrel, based on the Brent benchmark we’ll explain in a bit. That’s $3.85 below yesterday morning’s level and about $39 higher than where it stood a year ago.

Will oil prices go up?

No one can say for sure where oil prices will go next. Many forces shape the market—but at the core, it’s still about supply and demand. When risks like a potential recession or war ramp up, oil prices can change direction quickly.

How oil prices translate to gas pump prices

When you buy gas at the pump, you’re covering more than the cost of crude oil. You’re also paying for every step in the process, including refineries, wholesalers, taxes, and the markup your local gas station adds.

Even so, crude oil has the biggest influence on what you pay, often making up more than half the cost per gallon. When oil prices jump, gas prices usually climb right along with them. But when oil falls, gas prices often slip much more slowly—a pattern sometimes called “rockets and feathers.”

The role of the U.S. Strategic Petroleum Reserve

If an emergency hits, the U.S. keeps a backup supply of crude oil called the Strategic Petroleum Reserve. It’s mainly there to protect energy security during crises, such as sanctions, catastrophic storm damage, even war. It can also help cushion the blow when supply shocks send prices soaring.

It’s not meant to solve long-term problems. Instead, it provides quick relief for consumers and helps keep vital parts of the economy moving, like essential industries, emergency services, and public transit.

How oil and natural gas prices are linked

Oil and natural gas are two of the world’s primary energy sources. A big change in oil prices can affect natural gas by extension. For example, if oil prices increase, some industries may swap natural gas for some segments of their operations where possible, which which increases demand for natural gas.

Historical performance of oil

When looking at how oil performs, two main benchmarks stand out:

• Brent crude oil is the main global oil benchmark.
• West Texas Intermediate (WTI) is the main benchmark of North America.

Of the two, Brent gives a better picture of global oil performance because it prices a large share of the world’s traded crude. It’s also the go-to for tracking oil’s historical trends. In fact, even the U.S. Energy Information Administration now relies on Brent as its primary reference in its Annual Energy Outlook.

If you look at the Brent benchmark over several decades, oil has been far from stable. It has experienced sharp rises tied to wars and supply cuts, along with steep drops linked to global recessions and oversupply (called a “glut”). For example:

• The early 1970s delivered the first major oil shock when the Middle East slashed exports and placed an embargo on the U.S. and others during the Yom Kippur War.
• Prices fell in the mid-1980s due to lower demand and an influx of non-OPEC oil producers joining the market.
• Prices surged again in 2008 as global demand grew, but then crashed alongside the global financial crisis.
• During the 2020 COVID lockdown, oil demand plummeted like never before—pushing prices below $20 per barrel.

To sum up, oil’s historical performance has been anything but smooth. Again, it’s heavily influenced by wars, recessions, OPEC whims, shifting energy policies, and much more.

Energy coverage from Fortune

Looking to stay up-to-date regarding the latest energy developments? Check out our recent coverage:

• China may have a green energy overcapacity problem. Experts think AI can help solve it
• Trump’s ‘largest deregulatory action ever’ in the power sector will fuel the AI boom
• East-West pipeline was built in case Iran closed Hormuz. Tehran-backed militias still blasted it

Frequently asked questions

This story was originally featured on Fortune.com

This year marks the 25th anniversary of Is This It, the classic album by the Stokes, the rock band that turned the page from Gen X pop culture to something more distinctly millennial. It’s also a favorite album for this author and Glassdoor senior economist Chris Martin, who used the phrase in a recent conversation about his latest Millennial Report.

Millennials, he told me about his most recent research, have reached midcareer, their earnings have “for the most part peaked,” and they can expect growth to match inflation from here on out for the rest of their careers. The vibe is “we’ve made it,” Martin said, “and the long and the short of it is, it doesn’t feel good.” He described it as an “is this it?” moment.

I had to ask, was he channeling Strokes lead singer Julian Casablancas?

“Guilty as charged,” Martin said, adding that of course, he used to listen to the Strokes, and that vibe does sum up the modern age.

Martin’s preferred shorthand for the moment, borrowed from one of his generation’s defining bands, is hard to improve on: it’s the exact question a generation of newly arrived executives is quietly asking about the careers they spent 20 years building. Is this all there is?

A different kind of midlife crisis

Martin’s new Millennial Report lays out the paradox in stark terms. Millennials now make up 33% of the U.S. labor force — more than any other generation — and have nearly closed the management gap with Gen X (35% to Gen X’s 38%). More than one in four executives are now millennials, and they outnumber Baby Boomers in both management and leadership roles. Meanwhile, 76% of millennials say they’re actively questioning their career path, and 68% have delayed a major life milestone because of career uncertainty, according to Glassdoor Community polling from this summer.

The generation’s Glassdoor reviews tell the same story in a different register: burnout mentions run 44% higher among millennials than other generations, job-insecurity language is up 47%, and layoff mentions are up 54%. For millennial women, burnout mentions are 76% higher than everyone else — the widest gap in the analysis.

The obvious question is whether this just midlife, dressed up in generational branding. Martin acknowledged that it’s a bit hard to explain as Glassdoor’s review data is a snapshot, not a time series. The company can measure how much millennials mention burnout right now relative to other generations, but it can’t directly measure whether millennials feel worse than Gen X did in 2011 using the same reviews methodology. “We have to look at broad macro indicators,” Martin said. “Take a look back 15 years, at Gen X — things are a little worse in 2026 than 2011.”

Gen X hit midcareer management in roughly 2011, in the middle of what Martin calls “sustained economic recovery and growth” from the Great Recession, although some economists call that decade the “jobless recovery.” Millennials are hitting the identical stage after five years of inflation running above the Federal Reserve’s 2% target, Martin noted, alongside AI-driven anxiety about which jobs will survive the next few years of disruption. “Millennials are just not in the same moment,” he said.

That comparison comes with an important asterisk that belongs in any honest accounting of this research: Glassdoor’s review data is a snapshot, not a time series. The company can measure how much millennials mention burnout right now relative to other generations, but it can’t directly measure whether millennials feel worse than Gen X did in 2011 using the same reviews methodology — that gap has to be filled with macro indicators instead. “We have to look at broad macro indicators,” Martin said. “Take a look back 15 years, at Gen X — things are a little worse in 2026 than 2011.”

Millennials may simply be hitting classic career and family milestones a few years later than expected. “Not all doom and gloom,” Martin said, but he’s also unambiguous about which decade he’d have preferred: “I would rather have become a manager in 2011 than in 2026.”

The report proposes a central concept — “stability stacking” of layering skills, options, income and networks together so that no single job or disruption can knock them flat. This doubles as an indictment of the take-it-or-leave-it state of the current labor market, though, as it means in practice that soft-launching a new direction has to occur while staying employed, upskilling in AI-adjacent areas, pivoting laterally, or building visibility in a target industry before making a formal move. Martin also cautioned that the data are inconclusive about whether millennials can start businesses at the same rate other generations did.

“Stability stacking is a response to this moment of, ‘I thought it would feel better. I thought I could count on my career and feel stable.’ We’ve all been waiting for the bottom to fall out, and then a moment like, ‘maybe it’s not going to happen,’” he added.

What the data does show clearly is the emotional substrate underneath the strategy: “They feel really insecure in their jobs. Many are not in a position to be unemployed or strike out on their own.”

The trust deficit nobody predicted

The most surprising finding in Martin’s research cuts against his own hypothesis going in. He expected Gen Z — culturally coded as the generation most skeptical of corporate motives — to rate senior leadership harshly, given the perceived gap between companies’ stated values and their profit motives. Instead, Gen Z gives senior leadership higher marks and expresses more optimism about business outlook than any other generation in the dataset. The most pessimistic, most skeptical generation toward leadership is the middle management cohort themselves: the millennials.

Martin’s explanation is personal as much as structural: “Millennials have had a couple of big rug-pull moments in their career, so we are scarred from that experience — less likely to trust things.” The Great Recession hit as millennials entered the workforce; the pandemic hit as many were entering management. Two “once-in-a-lifetime” crises, arriving exactly when trust in institutions was supposed to be compounding, not eroding. It’s left a generation of managers feeling alone, together.

But what about the fact that the economy never tipped into the widely predicted recession in 2023, and a soft landing was pulled off instead? “We talk about a plane crash,” Martin said, “and it’s really obvious to tell when that happens. But landing a plane — the economy is not a single plane. It’s hard to tell if the landing process is behind us.”

Pressed on whether conditions are actually bad, Martin’s answer is neither alarmist nor dismissive: “Not as bad as we feared.” In other words, tables they turn sometimes.

For this story, Fortune journalists used generative AI as a research tool. An editor verified the accuracy of the information before publishing.

This story was originally featured on Fortune.com

Good morning. On Fortune’s radar today:

• The high price of war.
• Could Iran tank the market?
• Stocks down as bond yields enter “new era.”
• AI models often don’t know what time it is.
• What if “temporary” inflation is permanent?
• 63% of religious books on Amazon are AI slop, a study finds.

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This story was originally featured on Fortune.com

• In today’s CEO Daily: How AI is changing the nature of leadership
• The big leadership story: Uber CEO says layoffs will equal rider savings.
• The markets: In the red as Treasury yields and the price of oil rise
• Plus: All the news and watercooler chat from Fortune.

Good morning. Lee Williamson, Fortune’s Asia editorial director, writing from Macau, where we recently wrapped the inaugural Fortune Leaders Forum. We convened Fortune Global 500 executives, founders, experts, and policymakers to discuss how the convergence of multiple headwinds—AI breakthroughs, rising geopolitical tensions, changing demographics—is reshaping the global business landscape. In this era of volatility, we asked CEOs how they are building strategies for an unproven future, and how they make decisions before the path is clear. A recurring theme throughout the day was not just how AI is transforming companies, but how technology is changing the nature of leadership itself. Here are my three takeaways:

From efficiency to reinvention. ServiceNow’s Asia managing director Melissa Ries set the scene: the company’s research shows that while “about 60% [of companies] have AI agents; only 5% have redesigned their workflows.” Several leaders discussed the need to move away from thinking of AI as an efficiency tool to be bolted on to existing workflows, to a technology that mandates an enterprise redesign. “The biggest risk is [using] AI to improve today’s processes, so basically you get a better version of yesterday,” said Malina Ngai, Group CEO of 185-year-old health and beauty retailer AS Watson. “That loses sight of how we can use AI… to help us to reinvent how we serve our customers.” The company’s key metric to define success? A “customer love score,” which AS Watson sees improving as AI tools give staff more time to spend serving customers. Elsewhere, Feroz Sheikh, Syngenta Group’s chief information officer and chief digital officer, described how the agritech giant is evolving from monolithic systems and workflows to “modular pieces” so that supply chains and technology stacks can be realigned to adapt to fast-moving changes.

The talent equation. Walmart China’s president and CEO Christina Zhu built on Ngai’s comments, saying that “with AI, humans actually become more important, not less so,” highlighting how AI is helping the company’s merchandisers decide which products to stock. “The data only tells you what customers have chosen… it doesn’t tell you the unmet needs. That [only] comes with a deep human insight.” Zhu credited Walmart’s robust growth (its China business grew 20.7% last quarter, compared with Walmart U.S.’s 2.6% growth in the same period) to a combination of data, AI, and human decision-making that delivers customer satisfaction. “My boss is the Chinese consumer,” said Zhu. HP’s Asia head Michael Boyle also stressed the need to build systems that combine human talent with machine automation and not simply “re-engineering the same thing with AI.”  

The evolving role of leadership in the intelligent age. When knowledge and experience are commoditized, and high-quality analysis is available at the cost of a few tokens, what is the role of a leader—and what leadership quality is most valuable? IMD professor Tim Quigley argued it’s a CEO’s judgment, a sentiment shared by BCG’s Greater China chair Carol Liao, who described a new “premium” on high-quality decisions. ServiceNow’s Ries said that with intelligence automated, judgment is the new “scarce resource.” Becca Carroll, chief strategy officer of design agency IDEO, known for traditionally seeking “T-shaped” people who have deep expertise in one specific discipline, described how AI is creating the rise of the “comb-shaped person,” who has “a depth of expertise across a series of disciplines and can fluidly move between them.” Yuxiang Zhou, founder and CEO of Chinese tech company Black Lake Technologies, which builds AI agents for the manufacturing sector, said he is using agents to train his sales teams—and getting better results than human managers in blind testing. “How you define the relationship between you and AI is what will distinguish great leadership from good leadership,” he said. 

These conversations will continue at Fortune’s next Asia event, the Fortune Southeast Asia 500 Summit in Ho Chi Minh City on Nov. 3, where we will convene leaders of ASEAN’s largest companies to tackle the critical forces reshaping the region’s business landscape. Since I’m in Macau, the Las Vegas of Asia, I’d say it’s a safe bet that Southeast Asia’s AI transformation will be a key talking point. Apply to attend.  

Contact CEO Daily via Diane Brady at diane.brady@fortune.com

This story was originally featured on Fortune.com

The stablecoin boom has made it easier for people and businesses to move currencies across borders. But converting those digital dollars into money that can reach local bank accounts or digital wallets remains a practical hurdle. New York-based Fin.com is among the latest companies seeking to build the payment infrastructure that helps customers bridge that gap.

Cofounded by immigrant technology entrepreneurs Nabeel Alamgir and Mustafa Dar, Fin.com announced Tuesday that it has emerged from stealth with a $20 million seed round that closed in August. The financing was led by Expa and Uber cofounder Garrett Camp, with participation from Coinbase Ventures, Tenet Fund, the founders of Figure, Mesh founder Bam Azizi, Second Sight Ventures, and sovereign and royal family offices in the Gulf and Africa.

“We believe that money movement is like a plane taking off from one airport, but it has to land somewhere else,” Alamgir told Fortune. “We want to solve the last mile delivery problem.”

That mission inspired the name behind Fin.com, which serves as an abbreviation for “finishing the job.” Both founders have the company’s name tattooed on their bodies.

Fin.com sells white-label payment infrastructure to businesses, including financial services firms, consumer platforms and prediction markets. The company said its tools allow prediction market users to fund wallets from exchanges such as Binance and Crypto.com, while helping platforms move corporate funds across borders. Fin.com declined to identify specific clients but said they collectively serve more than 800 million users.

 Alamgir and Dar declined to disclose the company’s valuation.

Building from experience

Since Congress passed the Genius Act in July 2025, establishing a federal framework for dollar-pegged stablecoins in the United States, stablecoin activity has continued to expand globally. The sector’s combined market capitalization surpassed $305 billion in September, up more than 77% from a year earlier, according to DeFiLlama data. The growth has drawn a range of payments companies, including Circle and BVNK, along with Bridge, the stablecoin infrastructure provider owned by Stripe.

Alamgir and Dar acknowledged they have entered a crowded market, but said their personal experience informs Fin.com’s focus on certain regions. The founders have identified South Asia, Africa and the Middle East as key markets. In addition to its New York headquarters, Fin.com has offices in Las Vegas, Dubai, Dhaka, Bangalore and Lahore.

Both experienced the challenges of sending money abroad firsthand. Born in Bangladesh, Alamgir grew up in Kuwait before moving to New York as a teenager. Dar was born in Pakistan and lived in Saudi Arabia before moving to Los Angeles at age five. Growing up, both watched their parents struggle to send money to family overseas.

In 2023, Dar stepped away from 24/7 Jet, the private jet company he founded in 2012, to join Expa as an investor and explore opportunities in global finance and fintech. Around the same time, Alamgir had left Lunchbox, the enterprise restaurant-technology company he founded years earlier.

Alamgir wanted to apply his operational experience with payments to a broader challenge: gaps in financial infrastructure for underbanked people around the world. In late 2025, he flew from New York to Los Angeles to pitch Dar on the idea for Fin.com. The two quickly found common ground, and Dar soon transitioned from potential investor to cofounder. 

His colleague, Vitor Lourenço, founding partner at Expa, took his place as one of the seed round’s co-investors. For him, the fit was natural. “All of the Expa partners are immigrants. We grew up in different countries, so the opportunity of cross-border payments was very clear for us,” he said.

This story was originally featured on Fortune.com

“It’s not cost-cutting,” Bill Winters, the chief executive of Standard Chartered, insisted during a recent panel discussion. “It’s replacing lower-value human capital with the financial capital and the investment capital we’re putting in.” 

The words created a flurry of protests—“replacing lower value human capital” hitting a nerve for those nervous about an approaching AI “jobs apocalypse”. Winters was obliged to apologize, pointing out that Standard Chartered was investing heavily in retraining teams. 

How company leaders respond to the AI wave–and take their colleagues with them—is one of the most important issues for C-Suite leaders as they contemplate the year ahead. At Fortune’s CEO Forum this week on September 16, AI, workforce planning and return on investment will be a centerpiece debate. And that’s before any discussion on the fact that AI might kill us all in any case. 

“It’s fundamentally changing the way we work and our timescales and getting products to market quickly,” Kate Dohaney, the CEO of the U.K. mobile network, Giffgaff, part of the Virgin Media Group, tells me. “The question is not necessarily how do we bring down our human capital, but how do we train our people to do more, strategically, across the business? I’m not a CEO sitting back saying cut, cut, cut. 

“I’m not saying we don’t become more efficient as a business. But just like with any revolution that has happened in the history of humankind, we have to understand what are the next generation of skill sets? And I’m trying to get ahead of that and bring people on the journey and keep them excited and keep them curious as we navigate.” 

Dohaney is in a competitive market, not just with other mobile providers but with new entrants as well. Octopus (energy) and Revolut (banking) are both looking at offering mobile products as mass-to-consumer brands push towards “super-apps” which offer multiple services. Nubank, a U.S. neo-bank, now provides the NuCel mobile network in Brazil. 

“There’s a massive opportunity for telcos to get ahead and think about revenue diversification,” Dohaney says. “We have all these competitors getting into telco. We see Revolut, we see Monzo, we see Klarna. That does allow telcos to sit back and say: I can get a lot more creative, I already have this massive, amazing foundation with this great brand.” 

Earlier this year, I interviewed Erik Severinson, the Chief Commercial Officer at Volvo Cars, who spoke about brands needing to stand out in a world of noise. In a stadium full of white t-shirts, how does a company make sure it’s the red t-shirt that people notice? 

Dohaney has focused the Giffgaff brand on low cost and sustainability. It is a certified B-Corp, supports a number of charities, and three-quarters of the phones it sells are refurbished. “Giffgaff” is a saying in Scotland meaning “mutual giving”. 

“So how can we outmaneuver and capitalize?” Dohaney says about the new entrants in the mobile market. “We’re experimenting in fintech. Our strategy is focused on ‘fair play’, giving the next generation fair access and a leg up in life. So how do we enable new and different capital risk assessors for a young person who’s entering the workforce and having trouble finding a job, or wants to start their own business and has no idea where to start?” 

Service wars are coming–the mobile phone company that’s a financial trading and advice platform; the neo-bank that does telco; the table booking app that can find you flights to your next holiday destination. Human capital will be the vital component in winning the battle for the future, with a good dollop of AI thrown in.  

For the latest coverage and updates from Fortune CEO Forum, as well as insights into the companies on our list, visit this page.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

This story was originally featured on Fortune.com

A question has gripped economists studying inequality since at least 2011, when Occupy Wall Street split the country into the 1% and the 99%: who is actually wealthy in the U.S, and how did they get that way?

In 2014, Eric Zwick, Owen Zidar and Danny Yagan set out to find an answer. They weren’t the tenure-track economics faculty they are today (at the University of Chicago, Princeton University and UC-Berkeley, respectively) and all they had was a hunch and a key to the Treasury Department. Planet Money reported that they called themselves the “tax ninjas,” but they were essentially glorified interns: Zwick was living in his sister’s attic in Washington D.C. and going to work in the Treasury Department’s basement, where the ninjas attacked a trove of individual tax records that most academics never get to see.

The problem for economists had always been that the Internal Revenue Service kept individual tax returns and business filings in separate systems that had never been linked—there was no way to connect a company’s profits to the specific person who owned it and collected them. Zwick and Zidar spent months essentially making the two databases talk to each other. When they finished, Zwick told Fortune, he was stunned. 

When they made a table of total profits from pass-through firms for people in the top 1%, doctors were near the top, and so were auto dealers. “I’m like, this is not Jeff Bezos. This is not Stephen Schwarzman.” The American Dream still exists, in other words, but it isn’t the Wall Street billionaires or tech overlords who are mostly realizing it. It’s the everywhere millionaires all around you that you don’t even think about. 

Hence the title of Zwick and Zidar’s new book, The Everywhere Millionaire: Who is Really Rich in America and How They Got There. When I asked Zwick if he ever saw the classic high-school sports show Friday Night Lights, his eyes lit up as he named the local auto dealer who bankrolled the local Texas football team: “It’s the Buddy Garrity millionaire! It’s like, meet the real Buddy Garrity.” The book defines this class of millionaire as someone with at least $5 million in net worth who owns a single closely held operating business that generates most of their income. Their research found roughly 3 million of these in the U.S., concentrated not in Manhattan or Palo Alto but in mid-sized metros that rarely generate pitchforks in the press. They collectively hold 13 times the wealth of the entire Forbes 400, Zwick estimates. Put another way: for every member of the Forbes list, there are more than 4,000 private business owners who each have a net worth of at least $10 million.

The book’s favorite example is Dick Portillo, the Chicago food kingpin who opened a hot dog stand in 1963 having never cooked one before—and built the Midwest’s largest privately owned restaurant company by 2014—plus a 130-foot yacht he named Top Dog. Then there’s Karen Bentlage, who dropped out of Central Connecticut State University and built the nation’s second-largest tanning-bed distributor before reinvesting the proceeds into a regional waxing-salon franchise. The everywhere millionaires include a lot of dentists and beverage distributors, too, collecting profits through partnership structures that don’t appear in any billionaire index and rarely get a mention in political campaigns or cable television. 

courtesy of Macmillan

One of the book’s more unsettling arguments is that the everywhere millionaire essentially runs American politics: pass-through business owners make up roughly a quarter of federal elected officials and about 40% of state legislators, compared with 2% to 3% of the general population, Zwick estimates. The implication is that the American system of inequality works the way it does because the everywhere millionaires who dominate Congress are keeping the system that made them wealthy exactly the way it is. 

It’s a bipartisan issue, Zwick adds, noting “a bit more evidence [that] maybe the Republican elected officials are a bit more likely to come from this class than the Democrats. [But] there are a lot of Democrats, too.” He pointed to a provision from the most recent tax bill, which let clean-energy vehicle credits lapse while making a 2017 pass-through deduction permanent: “That benefits the auto dealers, many of whom are on the tax-writing committee of Congress.” He argued that Americans and the media are usually having the wrong conversation about wealth. “Where the power comes to make policy happen—it’s much more diffuse, and I think we’re not quite focused on it in the right way as a society.”

Zwick said he sees similarities between his and Zidar’s research and historian Patrick Wyman’s theory of the “American Gentry,” the “salt-of-the-earth millionaires” that far outnumber the coastal elites typically thought of as America’s true aristocracy. Zwick said Wyman is more polemical in connecting these elites to the rise of Donald Trump, but the idea is certainly “very resonant” and he and Zidar essentially have the receipts. 

When asked what made this cultural change possible, Zwick and Zidar point to a very clear turning point, decades in the past, long before the rise of Donald Trump.

Unintended consequences

During Ronald Reagan’s acting career, he limited how many films he’d make in a given year—earn too much, and the top individual tax bracket meant that he’d keep as little as 9 cents of every additional dollar. That experience shaped the tax-cutting instinct he carried into the White House in 1981, when the top individual rate stood at 70% and the corporate rate at 46%. 

Reagan found an unlikely ally in Bill Bradley, the former New York Knicks star turned Democratic senator from New Jersey, who was partnering with House Rep. Dick Gephardt to simplify the code by stripping out the loopholes and write-offs that mostly benefited the wealthy. Reagan and supply-side Republicans like former Buffalo Bills star Jack Kemp wanted lower rates across the board. The compromise was the Tax Reform Act of 1986, the biggest overhaul of the federal tax code in over three decades and, at the time, a rare bipartisan triumph. But it didn’t just cut the top individual rate down to 28% and the corporate rate to 34%—it also sweetened the tax treatment of partnerships, S-corporations and sole proprietorships, whose profits would pass directly to an owner’s individual return instead of being taxed twice, once at the corporate level and again as dividends. A new American Dream was being born.

Before 1986, C-corporations produced almost all business income in the U.S., but today, Zwick and Zidar found 95% of American businesses are pass-throughs. They employ half the country’s workers and generate the majority of business income. Almost by accident, the 1986 reform moved America’s business wealth onto the individual tax returns of the people who owned it. “Tax reform created the idea linking business owners to their businesses,” Zwick and Zidar write in the book, “bringing the stealthy wealthy into view for the first time.” It just took another 26 years, and two grad students in a Treasury department, for anyone to find it. 

When asked about Gen Z’s turn toward crypto, prediction markets and retail trading—what’s sometimes called “financial nihilism”—Zwick agreed that one takeaway from his book is certainly that the traditional path to success in America is obsolete. “Get a salary, a job and just work your way up within a company—[that] is not the path,” he said. But the operators in his data didn’t get rich by rolling the dice, he points out. There’s a “move slow and make things” strategy visible in stories like Portillo’s, who ran a hot dog stand himself for decades, long before it became an empire. The real key is owning the business and working so much that work-life balance essentially doesn’t exist. “He, like, never stopped making hot dogs.”

Paul Osterman, professor emeritus at MIT Sloan, has a book out that is something like the flipside of the everywhere millionaire thesis. Disposable Workers: The Transformation of Employment, the latest in Osterman’s long-running career examining the labor market, draws on a survey of more than 6,000 American adults and nearly 100 interviews with workers, employers and staffing agency professionals. A stunning 35% of the U.S. workforce, he found, falls into the category of what he calls “disposable” work—freelancers, contractors, gig workers and a category he calls “marginal workers”: W-2 employees hired with the implicit understanding that they won’t be around for long. 

Osterman traces this back to the Reagan era, but not specifically to the 1986 tax reform. Reagan’s famous 1981 firing of striking air traffic controllers was a sign of “open season on post-World War II employment systems,” he told Fortune. For whatever reason, he said, employers “do not invest in the great bulk of their workforce” in the way that they used to. 

When presented with Osterman’s findings, Zwick called them “very interesting” and agreed that the post-1986 tax code leaves employers with a much higher burden for salaried/wage-rate workers than other types of employees, which has “caused activity to leak out of the salaried worker bucket.” It discourages W-2 employment, he said, since contractors can structure their work for lowered tax rates and avoid the payroll tax by building their own pass-through entities. 

Katlin Smith and Bakari Akil both found themselves on the outside looking in, at earlier points in their careers, when they decided to become everywhere millionaires. 

Owning as the new American Dream

Neither Akil nor Smith fits Zwick’s definition to a T—he owns a small portfolio, she has already sold hers. But both got rich the way his data says most do now: by owning something outright, not by being paid to run someone else’s thing.

Smith didn’t set out to get rich, but rather, to fix a problem she had herself. In 2012, while working as a management consultant at Deloitte and essentially living out of her suitcase, she went looking for a snack that wasn’t unhealthy. A friend suggested that she clean up her diet, and she flashed back to her biology and business double major. She said she has a “scientist’s brain,” so she thought, “‘”Oh cool, an experiment, let’s give it a try.” 

courtesy of Simple Mills

Her experiment became Simple Mills, the snack brand that she built from nothing, bringing almond-flour crackers to a market near you. Like Portillo, who ended up selling to a private equity firm, Smith brought in a sponsor, Vestar Capital Partners, to scale the business and later exited to Flowers Foods for $795 million in January 2025. 

Smith told Fortune that she’s still involved with Simple Mills in a founder-and-advisory role, and her status has enabled her to push for personal passions, like a “non-UPF” verification for Simple Mills’ products, developed with the Non-GMO Project to flag how heavily processed a food actually is, not just what’s in it. Bringing more non-ultra-processed foods to market is “near and dear to my heart,” she said, even though she doesn’t want to make herself the face of any kind of movement. “I honestly really don’t love being a public example,” she said, adding that she would like to dedicate more time to philanthropy. 

Akil left Morehouse College in 2011 without finishing his degree and spent roughly two years afterward homeless, as he previously told the Wall Street Journal. He still remembers sleeping some nights in La Guardia Airport, where they’d let him stay on a bench if he was discreet and appeared to be waiting for a flight. At 25, he got a job at the startup Justworks and realized he wanted to be on the other side of the glass. “How did this happen to me?” he told Fortune about his state of mind at the time. “How do you get rich?”

He said he always assumed that being smart and hardworking was supposed to be enough on its own, and when it wasn’t, he spent close to a year reading everything he could about wealth-building. “The entire society was set up to help business owners be successful and employees to live a good life,” he said, adding that people who don’t own anything are “going to stay middle class and [that life] will be very precarious.” 

courtesy of Bakari Akil

Akil said he kept seeing the letters “LBO” (for leveraged buyout) and kept digging, eventually finding a Harvard Business School paper on “early-career” acquisitions. When he learned Columbia was about to teach it, he dropped everything to get into that class. “That’s how I learned to buy a company,” he said. He sensed a major wave developing as baby boomer everywhere millionaires started retiring. “It’s almost like an American imperative for people to look at these businesses,” he said. If the next generation chases startups instead of buying what boomers have left behind, “that’s an existential threat to the middle class.”

Other entrepreneurs are building a business off the act of businesses’ being sold. Chat Joglekar, a former Zillow employee, co-founded Baton, a marketplace for listing and buying small businesses. McKinsey estimates that 6 million small businesses, worth roughly $5 trillion, will need to change hands over the next decade as Baby Boomer owners age out, and fewer than one in three has a documented exit plan. “The whole adage in this market is that supply doesn’t realize their supply,” Joglekar told Fortune in a recent interview. Baton has published free valuations for 2 million U.S. companies and found that fewer than one in 10 owners can name their own company’s value within 10% of its market value. “It’s almost like you’re arming the rebels,” he said of his realization that knowledge is power. 

For his part, Zwick insists the book is not a polemic, and he resists the fatalism embedded in many accounts of American wealth and inequality. “I feel like saying the American Dream is not dead,” he said, “even if it’s less healthy than maybe it once was.”

This story was originally featured on Fortune.com

The biggest immediate impact of the Trump administration rolling back Biden-era emissions standards on power plants is it will keep more old coal and gas-fired plants viable for longer to help provide additional energy for data centers and the AI boom, experts said.

The U.S. Environmental Protection Agency (EPA) said Monday it finalized the repeal of emission-reduction mandates for power plants that were intended to combat climate change. The announcement came shortly after the National Oceanic and Atmospheric Administration announced that the 2026 summer was the warmest in U.S. history—about 3 degrees Fahrenheit above average.

Trump’s EPA said Monday that “emissions from power plants have no material impact on global climate change.” Environmental critics called that assertion a lie, arguing the rollback will cause thousands of unnecessary deaths from pollution and trigger many billions of dollars in additional health care costs.

But there is an argument that this strikes a balance between climate and the economy—“step back in order to take two steps forward,” said Dan Romito, managing director at Opportune overseeing sustainability. While renewable power can continue to expand, the energy sector is on the verge of leaps in cleaner, next-gen nuclear power and geothermal energy.

“It’s a Band-Aid for a lot of these data centers to figure out how to get replacement or complementary power,” Romito told Fortune. “We need a little bit of a stopgap here. It’s not an ideal choice. But coal can fill that bill for three, four, maybe five years. And that will allow the market to efficiently incorporate geothermal and nuclear solutions into the mix.”

In the meantime, the AI race is continuing, power projects are being announced without many getting off the starting line, and congressional permitting reform to expedite power—both clean and fossil fuel—appears unlikely to come to fruition this year. So something had to give, Romito argued. “This power is not going to magically come out of nowhere. You’re going to have to keep coal-fired power plants and gas-fired power plants online longer, not necessarily to fulfill the anticipated demand, but to meet what demand is currently today,” he said. “And you just can’t throw affordability and reliability out the window.”

The idea is this also will provide more certainty to hyperscalers that they can move forward. “It relieves a lot of the anxiety and the investor apprehension to invest in new modernized plants that are probably much more efficient as it relates to emissions,” Romito said, arguing that new gas-fired coal plants would be much cleaner than old coal plants.

The fight ahead

The 2024 Biden carbon standards for power plants aimed to require plants to either cut or use emissions technology to capture 90% of their climate pollution. In addition to undoing those standards, Trump’s EPA also is proposing to roll back its authority to regulate climate pollution from power plants, arguing that the EPA is not legally allowed to combat climate change. If successful, this could prevent future administrations from being able to regulate these emissions.

“We are cutting the red tape to deliver the largest power sector deregulatory action ever,” said EPA Administrator Lee Zeldin on Monday at the G20 energy ministerial in Houston.

“But we aren’t just stopping with the Biden administration’s overreach,” he added. “We also are proposing to rescind all remaining greenhouse gas emissions standards for power plants—all of them.”

Environmentalists called the Trump administration’s actions incredibly damaging.

“While wildfires rage, floods devastate communities, and families struggle to afford skyrocketing electricity bills and insurance premiums, the Trump administration is handing the fossil fuel industry a license to keep polluting,” said Sierra Club chief program officer Holly Bender. “This is full-throated climate denial while the climate crisis happens in real time and a shocking betrayal of the American public.”

Fossil fuel power plants are responsible for almost 25% of the nation’s total climate pollution, second only to the transportation sector. Early this year, the EPA overturned its own so-called endangerment finding from 2009, which determined that that carbon dioxide and other planet-warming gases are a threat to public health. The EPA also repealed ruled regulating emissions from motor vehicles.

The Trump administration contends the federal Clean Air Act does not specifically mention climate change and that the EPA should have no authority to regulate it, arguing that the “climate radicalism” of the Biden and Obama administrations were bad for business and energy affordability. Legal challenges are inevitable, just as with the earlier vehicle rollback.

“If you have a problem with the law, change the law,” Zeldin said.

“Will more data centers be using coal? That’s not something the EPA is going to dictate,” Zeldin added. “What we are going to make sure is that we’re following the law, that we are empowering that choice, and that we’re making sure the smartest decisions are made to unleash energy dominance in this country in every form.”

This story was originally featured on Fortune.com

The Trump administration’s efforts to slash diversity, equity, and inclusion (DEI) initiatives left another acronym on the chopping block: one museum’s $350,000 grant to replace its heating, ventilation, and air conditioning (HVAC) system.

Court documents from a recent lawsuit reveal the Trump administration’s Department of Government Efficiency (DOGE) slashed more than $100 million in projected funding distributed by the National Endowment for the Humanities (NEH), about half the agency’s yearly budget, on the basis of projects relating to DEI. DOGE employees tasked with overseeing the cuts, Justin Fox and Nate Cavanaugh, used ChatGPT to determine if proposals pertained to DEI efforts, filings show.

The American Council of Learned Societies, the American Historical Association, the Modern Language Association, and the Authors Guild filed a joint motion earlier this month arguing DOGE violated First Amendment rights and the Constitution’s equal protection clause by cuts made through illegal control of the NEH. Cancelling grants and funding on the basis of DEI constitutes discrimination on the basis of race, ethnicity, gender, and other qualities, the organizations claimed.

A spreadsheet presented by the plaintiff as evidence, shows a list of prompts Fox and Cavanaugh asked ChatGPT to determine if grants were DEI-related.

“Does the following relate at all to DEI? Respond factually in less than 120 characters. Begin with ‘Yes.’ or ‘No.’ followed by a brief explanation. Do not use ‘this initiative’ or ‘this description’ in your response,” the prompts begin.

Among the grants cancelled was a request by the High Point Museum, a history museum in North Carolina, for $349,000 to replace an aging HVAC system to “create a better preservation environment for the varied collections it houses,” according to the proposal contained in the spreadsheet. New equipment, the proposal said, could ensure long-term viability of making its collections accessible, and would be more energy-efficient. ChatGPT flagged it is “#DEI” in its response to the prompt.

“Yes. Improving HVAC systems enhances preservation conditions for collections, aligning with the goal of providing greater access to diverse audiences. #DEI,” ChatGPT responded, according to the spreadsheet.

According to Edith Brady, High Point Museum director, the museum received the grant and began the project, but it was later terminated. 

“We were able to recoup about 70% of the original award through the grant termination clause,” she told Fortune in an email.

The White House did not respond to Fortune’s request for comment.

DOGE’s offensive on DEI

The massive funding cuts were part of the Trump administration’s broader efforts to cull government-backed, DEI-related projectsI. On President Donald Trump’s first day of his second term, he signed an executive order banning diversity initiatives, following up in March 2025 with another proclamation targeting funding for programs his claims advance “improper ideology” and “divisive narratives.” 

DOGE, created as a special advisory and not an official agency on Trump’s inauguration day, was tasked with enforcing these efforts. The group’s de-facto leader, Tesla CEO Elon Musk, was tasked with identifying and cancelling contracts collectively worth billions of dollars. The cuts, which Musk said amounted to $200 billion, included 29 DEI training grants through the Department of Education totalling $101 million DOGE claimed. In April 2025, the Pentagon, under Defense Secretary Pete Hegseth, purged nearly 400 books from the U.S. Naval Academy library that it claimed related to DEI.

Musk left DOGE at the end of May 2025, following the end of his 130-day stint as a special government employee. According to Office of Personnel Management director Scott Kupor, DOGE ceased to exist as a “centralized entity” as of November 2025.

These sweeping cancellations extended to NEH funding. Of the 1,163 grant proposals DOGE analyzed via ChatGPT for DEI-related content, 1,057 were flagged, and just 42 were kept.

NEH cuts appeared to go beyond DEI

Some of the cancelled grants appear to have little to do explicitly with DEI. ChatGPT appeared to flag a project on literary agents and the corporate structure of the publishing industry as DEI, as well as a center for AI ethics, including for research on “AI-based technologies for eldercare,” and a project to collect resources on the history of Italian-American immigrants.

According to the spreadsheet, 11 grants ChatGPT analyzed related to installing updated HVAC equipment, but just two, including the High Point Museum proposal, were flagged as DEI. The second, asking for funding to improve building infrastructure of the Shelburne Museum in Vermont to address climate change, was flagged as DEI for “addressing environmental sustainability in cultural heritage preservation.”

Michael McDonald, acting chairman of the NEH appointed by the Trump administration, appeared to indicate the cuts went beyond DEI. In an email included in court filings, McDonald wrote to to DOGE staffer Fox that many of the projects on the chopping block were “harmless when it comes to promoting DEI.”

“But you have also told us that in addition to canceling projects because they may promote DEI ideology, the DOGE Team also wishes to cancel funding to assist deficit reduction,” he said. “Either way, as you’ve made clear, it’s your decision on whether to discontinue funding any of the projects on this list.”

McDonald did not immediately respond to Fortune’s request for comment.

But the outcome of these cuts may have had little impact on the federal deficit DOGE set out to reduce. Cavanaugh, one of the DOGE staffers tasked with overseeing these cuts, said in deposition pertaining to the recent lawsuit the advisory failed to slash the government’s budget gap.

“Did you reduce the federal deficit?” the attorney asked.

“No, we didn’t,” Cavanaugh said.

This story was originally featured on Fortune.com

In the check-out line of your local grocery store, there’s a nearly one-in-three chance someone there has used an app like Klarna or Affirm to finance their purchase of produce, milk, and eggs at some point. Their use of buy now, pay later could mean your groceries are about to cost more, economists have found.

A study from the Washington University in St. Louis, which will be published in the next issue of the Management Science journal, found that as more consumers turn to buy now, pay later to purchase their necessities, retailers may actually increase prices and slash inventory as a result. 

These types of purchases have become especially appealing for smaller, but necessary shopping trips. A Lending Tree survey of more than 6,000 U.S. consumers published in July found 29% of Americans self-report using buy now, pay later loans for groceries, nearly double the 14% from two years ago.

It’s all part of a bigger trend of buy now, pay later becoming an increasingly appealing option for consumers as they face an affordability crisis of increasing healthcare and childcare costs, as well as stubbornly high inflation, with 91.5 million Americans using apps like Klarna, Affirm, and Afterpay to finance purchases. Purchases with these apps grew 20% from 2021 to 2025, according to the Federal Reserve Bank of Richmond, though they still make up only about 1% of credit card transactions.

Researchers led by Panos Kouvelis, a professor of supply chain, operations, and technology at WashU’s Olin Business School, set out to find what exactly would make this model appealing to retailers, who have to pay merchant fee for each buy now, pay later transaction. The study authors developed an economic model that captured not only consumers’ willingness and ability to pay for goods using buy now, pay later, but also retailers’ expected profits. They found that retailers increased their sticker prices to offset the merchant fee, meaning in some cases, customers paying in-full effectively subsidized the customers who financed their purchases, and all consumers saw higher prices.

“Retailers, as a result of accepting these kinds of payments, they are going to increase prices, which basically means that all of us are going to pay for these practices that are out there,” Kouvelis told Fortune.

Why buy now, pay later might sting consumers and retailers alike

Retailers are feeling this pressure to raise prices particularly because of consumers’ growing reliance on loans to pay for basics like groceries. Buy now, pay later was originally intended for large discretionary purchases like furniture or gaming consoles. These products have higher margins, meaning that for the retailers selling them to consumers financing the purchase, they would still be profitable even after paying the merchant fee. Necessities like groceries, however, have much thinner margins. 

 A sign of economic strain for the consumer, this shift in how people are financing their purchases is also likely less appealing to retailers, who are pressured to raise prices to try to maintain tight margins on these necessities. If retailers are finding some goods are no longer profitable, they may stop stocking them, giving fewer choices to consumers.

“Why does it really make sense for the retailer,” Kouvelis said, “unless they are hoping that as a result you are buying a much larger basket of goods and therefore they are making money on other products.”  

Buy now, pay later’s hidden dangers

There are broader concerns around consumers using buy now, pay later for basic purchases. This Fintech is largely unregulated and historically, these companies have not reported debt to credit agencies. As a result, there’s a growing pile of “phantom debt” for some consumers, who may carry five to 10 loans for buy now, pay later at a given time, Kouvelis explained. Lending Tree fund 47% of buy now, pay later users were late paying back a loan in the last year.

To be sure, this debt is not large, about $135 on average, and consumers are more likely to pay back debt from short-term financing first, but Kouvelis noted even without widespread economic impacts, the potential dangers of buy now, pay later are present for consumers and retailers alike.

“There is a certain fear,” he said. “There are some people that are living at the edge that are really overborrowing, and nobody knows about it. Of course, that’s bad for them because at some point time things are going to catch up with them …. For the retailers, if these people are coming your way and they’re lowering your margins, also they have an effect in terms of your profitability.”

This story was originally featured on Fortune.com

On Thursday, the European Securities and Markets Authority, in its biannual risk report, finally let the cat out of the bag. The report concluded what was on the tip of many tongues. The Authority wrote that “A growing number of incidents illustrates that prediction markets are rife with insider trading.”

The idea that insiders, with advanced knowledge of events, hold the whip handle in prediction markets, runs counter to claims made by their promoters, who include President Trump and Donald Trump Jr. And the Trumps are not alone. The pantheon of prediction market promoters also includes Michael S. Selig, the Chairman of the Commodity Futures Trading Commission (CFTC), the U.S. agency tasked with regulating prediction markets. Talk about a fox in the hen house. Never mind.

The champions of prediction markets portray them as pipelines to the truth. Enthusiasts insist that the prices of the traded assets reveal the true probabilities of the different events in question. That works well for things like the weather, where no one trading in the market can influence, for example, the chance that a hurricane will make landfall in Hawaii before 2027. But we should doubt the truth-tracking prowess of prediction markets when Big Players can both bet in the prediction market and influence the events in question. 

On the prediction market Polymarket, for example, you can buy an asset that pays one dollar if the Fed’s interest-rate policy will remain unchanged in September. If members of the Fed’s FOMC, which sets interest-rate policy, go on Polymarket to trade in that asset, we cannot pretend its price is somehow revealing an objective truth about the world.

What’s that, you say?  No Fed officials would stoop so low?  Well, in 2021, as reported in Fortune, two Fed officials were found to have engaged in “extensive stock trading in 2020, when the Fed was spending trillions of dollars stabilizing financial markets and boosting the economy.”  They were influencing the policies that determined the value of their investments. One of the two “had invested in funds that owned mortgage-backed bonds, the same kind that the Fed” had been scooping up. The episode suggests that, as David Hume advised in 1742, we had better assume that some policymakers are not above profiting from the policies they craft, and that they will even craft policies to make a profit.

Donald Trump Jr. gives us further cause for pause. After Donald J. Trump won the 2024 election, Junior’s investment firm, 1789 Capital, bought shares in Polymarket. As The New York Times reported, “the government had banned [Polymarket] from taking monetary wagers from U.S. residents, but last year a federal regulator granted it an operating license in the United States.” Worth under a billion when 1789 first invested, Polymarket is now worth $21billion. This is naked Big Playerism.  The son of the President invests in a business; the rules somehow change during his dad’s administration; and presto, its value climbs to wild new heights.

When Big Players are involved, as they are in prediction markets, red lights should flash. Big Players damage the truth-tracking power of the system they influence, including prediction markets. Small players rationally invest less in tracking objective truth and more in tracking the Big Player. Fed officials, as well as US Presidents and their close associates, are Big Players. They have the power to extinguish the truth-tracking prowess of prediction markets like Polymarket and Kalshi. This makes the future murkier and rational planning more difficult.

Welcome to the age of Big Players. They run the show. We pay the price.

Steve Hanke is a Senior Contributing Columnist at Fortune and Professor of Applied Economics at Johns Hopkins University. He served on President Reagan’s Council of Economic Advisers. Roger Koppl is Professor of Finance at Syracuse University’s Whitman School of Management. He is the author of Big Players and the Economic Theory of Expectations (2002).

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

This story was originally featured on Fortune.com

AI is supposed to make our lives easier by taking the drudgery out of everything and yet years into this new future, more time than ever is being wasted with legal nonsense that keeps gumming up the internet. It’s easier than ever to save humanity a billion and a half hours, and it won’t take a single technological breakthrough — just common sense.

The digital gunk was introduced mostly by lawyers and politicians. Every company facing a lawsuit or a fine independently landed on the same defensive move — senseless consent banners and agreement paragraphs. Nobody asked for it. They just appeared on every website, app, and digital interface, forcing everyone to waste time clicking through useless buttons. Over time, regulations have piled up with no end in sight, leading to more buttons, more banners, and more waste.

Now with ChatGPT and Claude integrating into our daily lives, we run the risk of even more waste. Before lawyers start taking out their red pens, here are five fixes we should address to clear the clutter.

1. To cookie or not to Cookie. Two years ago, you could at least pretend this was a European problem. Now, every site on Earth greets you with a pop-up that takes up your whole phone screen with 15 toggle switches and a “Confirm choices” button. Regulations multiplied, and now consent banners are everywhere. We should just have one universal consent dashboard for different kinds of sites on each device – set it once, apply it to every site, and move on with your life.
2. Two-factor authentication everywhere. Security is important and it used to mean one extra step. Now there’s a six-digit code, an email confirmation, and a push notification connected to a device in the other room. There are so many new cybersecurity features that there’s a whole market full of authenticator apps who generate codes for you every 30 seconds, every day. Even streaming an episode of your favorite show in an airport requires 2FA. Apple has it right with Passkeys — we need to move to a full biometric system and end the billions of daily passcodes that gum up our texts and emails. 
3. Click the images with a fire hydrant. CAPTCHAs are another singularly annoying form of digital torment. Miss one blurry edge of the fire hydrant in a grey corner? You’re not human! Cars, trucks, crosswalks, grainy bicycles, you name it – we’re stuck playing games to prove we’re human as AI gets smarter by the hour and likely will do a better job at answering these questions. Extend passkey to these checks and move on.
4. Make a new account with us before you can see our content. Once upon a time, you could search something up and read an article about it. Now you have to register, verify your account in an email, set up a password following very inconsistent and specific rules about capitalization and symbols – and after all that, check the mandatory red box to consent to spam updates or five other newsletters that have nothing to do with you. There should be an AI plugin that autofills everything for you; we shouldn’t be wasting time plugging away our email and shipping addresses 10 times a day. And yet we are.
5. Unlimited terms and conditions. There’s always a smaller font for lawyers. I used to think they were long, but now they’re sprawling constitutional updates that you have to scroll to the bottom of in order to proceed to your app or webpage. This happens with every app update, every new product you’re connecting to your phone, every digital integration across your platforms. And it’s only gotten worse with AI, crypto, and new privacy laws. There should just be a plain English summary. Maybe an independent group should read all of these things in detail and provide a rating from “go ahead” to “don’t even think about signing” as average people really can’t possibly give meaningful consent.

Notice how ChatGPT and Claude don’t waste your time with all of this silly stuff as of today. But how long before lawyers get to a question like “What is the best remedy for a sprained ankle?” Instead of getting a simple answer, your chat will respond with: “I would love to answer your question, but first can you sign in? And then next, can you please agree to my terms and conditions, and would you like to hear them? And can we use your information to help others or not? And by the way, ChatGPT is not a healthcare professional and is not liable for any actions of the user following generated advice.” Zip-lining or bungee jumping will seem easier.

It sounds ridiculous but it is just a few lawyers and one class action case away. Underlying these measures are real issues on tracking, security, and legal liability but the way they are being solved today on the open web is simply a waste of humanity’s time.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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For more than a decade, a trend has emerged in standardized testing data for students in Utah. After years of increasing reading and math scores, results from the state’s National Assessment of Educational Progress testing for fourth- and eighth-graders have shown a steady and continuing downturn. 

Neuroscientist and former teacher Jared Cooney Horvath noticed the inflection point of this data coincided with the implementation of Student Assessment of Growth and Excellence (SAGE), the state’s first computer-adaptive test.

“Before 2014, computers were in schools, they were just peripheral,” Horvath told Fortune. “After 2014, every school had to have digital infrastructure in order to take the state assessment.”

According to Horvath, author of the 2025 book The Digital Delusion: How Classroom Technology Harms Our Kids’ Learning—and How to Help Them Thrive Again, Utah’s test score data isn’t a fluke; it’s part of a global trend of plummeting test scores that have coincided with the rise of easy access to computers and tablets in the classroom.

Earlier this year, Horvath testified before the U.S. Senate Committee on Commerce, Science, and Transportation, arguing the technology’s impact on more than just test scores, but on the cognitive capabilities they are intended to measure. He said for the first time in modern history, today’s generation has failed to outperform their parents on standardized assessments. In other words, Gen Z is the first generation to be less cognitively capable than their predecessors.

Citing data from the Program for International Student Assessment taken from 15-year-olds around the world, Horvath revealed it’s not just a dip in test scores, but also a correlation between these slumping scores and how much time students spend on computers, such that more time in front of screens was associated with worse scores.

Technology was put in schools in a bid to help them learn. Instead, Horvath said, computers had an adverse impact on learning.

Horvath blames educational technology (edtech) for these atrophying skill sets, arguing that at the turn of the 21th century and through its first decade and a half, tech companies and advocates pushed a false narrative that the education system was broken, but computers could fix it. Instead, Horvath said, the plan backfired.

“This is not a debate about rejecting technology,” Horvath said in his testimony. “It is a question of aligning educational tools with how human learning actually works. Evidence indicates that indiscriminate digital expansion has weakened learning environments rather than strengthened them.”

The rise of edtech

Edtech found its roots in U.S. schools in 2002, when Maine became the first state to implement a statewide laptop program in some elementary and middle schools. In its first year, the Maine Learning Technology Initiative distributed 17,000 Apple laptops to seventh-graders across 243 schools. By 2016, 66,000 Maine students had laptops and tablets.

By 2024, the U.S. had spent more than $30 billion putting screens in classrooms, with school districts making deals to buy tech at a discounted rate. A Florida state appropriations report from 2003 noted a four-year, $37.2 million lease from Henrico County, Va., for 23,000 Apple computers for high school students. Oklahoma City Public Schools minted a $25 million contract with Dell for 10,000 laptops and wireless carts.

According to Horvath, these deals helped some tech giants find footing after rocky product launches, in particular Google. After the shaky rollout of its Chromebook, the low-cost computers with free Google apps found their way into schools and by 2017, accounted for more than half of digital devices sent to schools. Horvath claimed Google sold these laptops to schools to help it recoup costs on the product. Google did not respond to Fortune’s request for comment.

The snowballing of edtech in classrooms was associated with an emerging narrative on how tech impacts learning, Horvath said: Education was broken, and computers could provide adaptability to students’ differing learning needs. With knowledge at their fingertips, students could be empowered to learn all by themselves.

To Horvath, these pushes toward screens in classrooms was an attempt to solve a problem that did not exist. At the turn of the century, achievement gaps across race and gender were closing, and test scores were rising, he said.

“Everything was looking good,” Horvath said. “So by what argument were they saying education was broken? There was no argument. They were just making it up to try and get people fomented to say, ‘I guess we need a new tool in there.’” 

Edtech’s weakness: the ‘transfer problem’

A close look at the history of edtech reveals criticisms of the pedagogy that go back nearly 100 years. 

In the 1950s, legendary behaviorist B.F. Skinner debuted his version of a “teaching machine,” based on the 1924 invention of Ohio State University psychology professor Sidney Pressey. The contraption was loaded with a piece of paper with questions, and students pressed keys indicating the correct answer, at which point another question would appear. Both Pressey and Skinner ran into similar problems, though, failing to implement the technology in schools. Educators weren’t convinced of the machine’s benefit, which prioritized individually paced learning not conducive to students of the same age moving through a grade level at the same time.

Later, in a letter to Skinner, Pressey would concede there was a massive pedagogical limitation to the device: Students learned how to master the machine, but not the subject matter.

“The reason they all quit was the transfer problem,” Horvath said. “They found that kids would be very good so long as they were using the tool, but as soon as they went off the tool, they couldn’t do it anymore.”

Edtech’s AI revolution

The results seem to follow, no matter what decade the technology is found in. Today’s teaching machines have taken the form of AI, and educators are once again concerned the technology will encourage students to master the use of bots at the expense of their own critical thinking and synthesis skills. 

 A Pew Research Center survey published earlier this year found more than half of U.S. teens use AI for their schoolwork. A Brookings report from January suggested students were abusing the technology, using it to cheat as opposed to really learning.

“Students can’t reason. They can’t think. They can’t solve problems,” said one teacher interviewed for the study.

Horvath was inclined to agree. He said the best learning happens where there is friction, or when a student needs to grapple with a problem and work through it. AI is most effective when experts use it, he argued. Someone with mastery of a skill knows how to deploy a certain AI tool and then fact-check its output. A student, however, doesn’t have mastery and looks to AI only for shortcuts.

“The tools experts use to make their lives easier are not the tools children should use to learn how to become experts,” Horvath said. “When you use offloading tools that experts use to make their lives easier as a novice, as a student, you don’t learn the skill. You simply learn dependency.”

Some politicians are taking matters into their own hands. New York City Mayor Zohran Mamdani doesn’t want students to engage with the technology at all, announcing earlier this month a one-year moratorium on student-facing generative AI tools like chatbots.

But a ban may not be necessary to get the outcome that best serves students, Horvath suggested. As schools begin to introduce AI literacy courses for their students, Horvath said there are ways for learners to develop a balanced relationship with the emerging technology. Edtech advocates have confused curriculum with pedagogy, he suggested. While curriculum refers to what is taught, pedagogy is how that material is taught. Instead of teaching students about computers—where technology would be in the curriculum—edtech has become about teaching a subject matter through computers, a pedagogy that has shown it’s not effective.

“If you really want kids to be good at AI, continue to teach them stuff. Teach them math, teach them literacy, teach them numeracy, give them a general education,” Horvath said. “So when they’re older and experts, they can bring meaning to that machine and now use it to make their lives easier, as opposed to trying to help them figure out how the world works.”

A version of this story was published on Fortune.com on March 1, 2026.

More on technology and education:

• Techlash grows in education: ‘My daughter went to middle school and was sent home with a screen addiction in her backpack’
• America’s math and reading scores tanked after schools ditched textbooks for screens—and AI could worsen the brain rot
• Wealthy parents are buying their kids $75,000 AI schooling with guardrails as schools grapple with a literacy crisis
• 84% of students use AI for homework. Only 3 in 10 schools have rules for it

This story was originally featured on Fortune.com

Jamie Dimon believes that to win big, you often have to think small—or at least in small teams.

In his annual shareholder letter this year, the longtime JPMorgan Chase CEO said the company’s “real competitive battles” are fought on a more granular scale.

Despite JPMorgan having more than 300,000 employees worldwide, he claimed the best way to fix a problem is to assign it to a small but capable team fully dedicated to the task, including in several areas like AI, marketing, and others.

“The teams needed to tackle these challenges should be small and authorized with the decision-making ability to move and act like Navy SEALs or the Army’s Delta Force,” wrote Dimon.

Otherwise, a larger group trying to solve a problem won’t give it the priority it needs to be resolved quickly. When a task is only 1% of a person’s job, you don’t get the same results as when everyone is 100% focused on the same objective, he explained.

“Very often when a management team wants to accomplish something new, like create a digital account opening process that cuts across virtually every area, everyone on the team says, ‘We’ll get it done,’ meaning they will add it to the long list of tasks already on their plate,” Dimon added.

Science mostly backs up this theory. More than 100 years ago, French agricultural engineer Max Ringelmann discovered that an individual pulled a rope with more force alone than they did in a group, which he theorized was partly because people expect their teammates to pick up the slack. 

In 1979, another study by Bibb Latané, Kipling Williams, and Stephen Harkins of Ohio State University on “social loafing” found that individual effort dropped sharply as the group cooperating on a task grew.

The researchers argued this psychological tendency comes about because people assume their teammates aren’t trying hard; they set lower personal goals when help is available; and they feel less individual accountability when their contribution isn’t evaluated or rewarded separately. The researchers concluded that at least one of the keys to preventing social loafing is restoring individual responsibility within a group. 

Business leaders have tried to tackle the issue of social loafing for years. In the early days of Amazon, founder Jeff Bezos instituted a “two pizzas” rule that claimed any team that can’t be fed by two pizzas was too big.

In 2023, Mark Zuckerberg doubled down on “efficiency” by laying off thousands of employees and flattening the company’s management structure, which he later said led the company to move faster.

In the age of AI, tech companies are reducing their workforces while still expecting the same results or better. Block earlier this year laid off 40% of its workforce partly owing to the progress of AI tools, according to CEO Jack Dorsey.

There’s some data that shows startups in the AI space are getting smaller. A study by researchers at Harvard Business School and nonprofit business school INSEAD found that companies building AI-enabled products employ 15% fewer entry-level workers than the traditional startup. Some startups have even used AI to bring in more than $1 million a month with teams of fewer than 20 people.

For Dimon, winning in business demands “speed, agility, and relentless execution,” and creating small teams is the best way to deliver it.

“This is trench warfare; it’s about fighting for every inch, moving quickly and getting things done,” he wrote.

A version of this story was published on Fortune.com on April 6, 2026.

This story was originally featured on Fortune.com

“What, like it’s hard?”

While it’s an iconic line from her career-making film Legally Blonde, it’s also a mantra Reese Witherspoon lives by. The actress-turned-media-company owner has long had the grit required to ideate, found, and ultimately sell a near-billion-dollar company that flipped Hollywood’s script on its head.

By the time Witherspoon was 34, she had spent two decades inside the movie business, she had seen enough. The scripts landing on her desk in 2011 were, in her words, “abysmal [and] really demeaning. One project built around a man with two women “just vying for his affection” really pushed her over the edge because of its “gross jokes and scatological humor,” Witherspoon said on an episode of Founder Mindset by Harvard Business School’s Reza Satchu earlier this year.

“I called my agent, and I said, I’m not auditioning for this, and I’m not interested,” she said. In response, her agent told her every actress in Hollywood was fighting for those two parts because there was nothing else. 

So Witherspoon set out on what she called a “listening tour,” visiting the heads of all seven major studios with a single question: How many movies are you developing right now with a female lead? The answer, for the most part, was none. One executive even told her the studio had already made one movie “with the woman at the center of it” that year, and couldn’t make a second.

“First I got mad, and then I was like, Wait—this is a huge white space,” she told Satchu.

With that, Witherspoon set out on her journey to develop Hello Sunshine, a movie company “made by and for the next generation of women” with the mission of putting female stories at the center of film, television, podcasts, books, and other media.

The financial scare that shaped a founder’s mindset

Witherspoon grew up in a household that hit “some pretty bad places” with money in her teenage years, thanks to her father’s “spending issues,” she said. At 16 or 17, she was pulled in to help. The experience shaped her worldview, which has driven every professional decision since.

“I was always had this idea that no one’s coming to save me,” she said. “I didn’t have a financial safety net… my parents were loving and kind, but they didn’t have the means to send me to college. I knew I was going to have to do it on my own, and if I didn’t succeed, there wasn’t anybody coming to save me.”

That same mindset forced her out of Stanford after roughly a year.

“I think people try to paint my dropout story like, I’m some sort of wunderkind that had some great business,” she said. “But it was literally just I couldn’t pay for—I couldn’t afford tuition.” 

Tuition, she remembered, was about $33,000 a year. But acting jobs paid. Years later, when she realized the reality of the studio system, she used the same mindset: If she didn’t build the company, no one was going to build it for her.

From Pacific Standard to a $900 million exit

Witherspoon’s first formal attempt at fixing Hollywood’s woman problem came through Pacific Standard, the production company she ran with Australian film producer Bruna Papandrea. 

Their first two book options—Cheryl Strayed’s Wild and Gillian Flynn’s Gone Girl—both hit No. 1 on the New York Times bestseller lists. The film adaptations, plus the HBO co-production Big Little Lies, racked up “three Oscar nominations and over $600 million in the box office,” she said. (Witherspoon retained control of Pacific Standard after parting ways with Papandrea in 2016.)

But the economics didn’t work. 

“I was only working for producer fees. I had four employees, and I was only breaking even,” she said during the podcast interview. “The overhead was eating me alive. That’s not a real business.”

The fix was Hello Sunshine, the mission-driven media company Witherspoon cofounded in 2016 with Strand Equity’s Seth Rodsky, initially as a partnership with AT&T’s Otter Media. It’s main mission was to put women at the center of every story. 

Hits from Hello Sunshine followed quickly, including Big Little Lies, Little Fires Everywhere on Hulu, and The Morning Show on Apple TV+, and the influential Reese’s Book Club.

In August 2021, Witherspoon sold a majority stake in Hello Sunshine to a Blackstone-backed venture led by former Disney executives Kevin Mayer and Tom Staggs in a deal that valued the company at roughly $900 million. Witherspoon and CEO Sarah Harden retained significant equity and board seats, Blackstone announced at the time. 

But for Witherspoon, that sale number is less the point than the proof of concept it offers.

“I hope that people out here…will think ‘I’m going to have the next Hello Sunshine,’” she said. “Because it is possible.”

A version of this story was originally published on Fortune.com on May 17, 2026.

This story was originally featured on Fortune.com

This fall, students are making their way back to school filled with the possibility that comes with a fresh academic year. Some high school seniors will dive into college applications, some will use this year to prepare to enter the workforce, and some will weigh the countless other pathways available from certifications to military service. All of them will be acutely aware of the weight their decisions will hold for their futures. 

However, the stark reality is that America’s leading businesses say high school graduates aren’t as prepared as previous generations, citing that they can execute assignments but struggle to think critically and navigate ambiguity at a time when technology is rapidly reshaping work. Educators see similar gaps. 

Recent research shows only 40% of hiring managers say it’s easy to find entry-level candidates with the skills they most need: the ability to communicate clearly, work in teams, solve problems, manage projects, and understand the fundamentals of financial decision-making. 

These are gaps our nation can’t afford to ignore. Students are graduating from high school without a clear understanding of how organizations function, how money flows, and how ideas become opportunities. Today, fewer than 20% of high school students take a business course—and when they do, it’s often siloed as an elective or introduced as a path to a business degree rather than foundational for necessary workplace skills. 

Our own personal upbringings highlight the long-standing disparity. In rural Oklahoma, Neil’s high school sorted students early into college or trades. His parents – both small business owners – understood their tradecraft but had little expertise in how to grow a business. Ultimately, Neil chose to pursue the “college track,” where college-bound students completed academic courses with few opportunities to build practical, hands-on skills, while those on the “trade track” were rarely exposed to business know-how that could help transform their expertise. 

Greg’s parents worked on the assembly line in an airplane manufacturing plant in Williamsport, Penn., but had dreams for more. They tried multiple times to start businesses, including a corner store, and each effort failed because they lacked access to the tools and skills needed to build a business model and run it effectively. 

These experiences are not isolated. To sustain our nation’s competitiveness and economic growth, business literacy is no longer optional—it’s critical to achieving full participation, and personal success, in today’s society.

Beyond the practical skills of budgeting, saving, and investing, students need to understand how our economy works, how organizations make decisions, how to evaluate risk, how to bring an idea from concept to execution, and how to lead a team. 

For the student interested in visual arts, add business education and the same student learns how to sustain a creative enterprise. For the student interested in computer science, business education leads to an understanding of how to bring innovations to market. Add it to the skilled trades and students gain the tools to run a small business. 

There are promising developments to change the status quo. Employers are raising their hands to partner with schools. States are strengthening requirements for financial literacy—the latest report from the Council for Economic Education counts 39 states that now require students to take a course in personal finance to graduate. And students are advocating for learning that feels relevant to their futures. 

When students have access to this learning, the impact is clear. Business Professionals of America, DECA, and Future Business Leaders of America show what happens when students engage in business competitions and leadership development. Students build confidence, teamwork skills, and problem-solving abilities they carry into college and careers. 

But too often, those opportunities depend on where a student lives, what their school offers, or even a student’s own plans. 

Preparing Students for the Modern Economy 

Both of us have seen firsthand how earlier exposure to business education could have changed lives. 

It’s why our organizations are combining decades of education and business expertise to launch a solution to prepare high school students. 

Now available in schools nationwide, AP Business with Personal Finance brings this learning to more classrooms and more students. The course combines rigorous academics with relevant, employer-informed content allowing students to earn both college credit and employer recognition. By pairing business and personal finance, students move beyond just learning how to manage money to understanding how to create opportunity. For example, students are currently working through their first “Business Canvas” projects to develop and pitch a business of their choosing. 

When high-quality academic programs like Advanced Placement are made broadly available to students through new coursework, opportunities expand, especially for students who have historically been underrepresented in advanced academic programs. AP Business with Personal Finance is part of College Board’s AP Career Kickstart, a new group of courses that can be tailored to fit into existing career and technical education (CTE) programs. 

No student should have to choose between mastering their craft and understanding how to translate that mastery into economic mobility. By making business and financial literacy a part of the high school experience, we can equip every student with the knowledge, skills, and confidence to navigate, adapt, and succeed. 

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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Corporate governance is being stress-tested, not at the margins, but at the level of its underlying architecture.

The modern board model was shaped in the industrial era, when companies were hierarchical, risks were more contained, and change moved more slowly. Governance followed that structure: information flowed up through management, and oversight flowed down from the board.

That model still defines how most boards operate today. But the environment it was built for has changed.

What’s emerging is a structural tension: a governance architecture designed for a vertical world operating in a horizontal risk environment.

Many of the most consequential risks today move horizontally: across functions, across geographies and, increasingly, across organizational boundaries.

Cyber incidents rarely remain a technical issue. They quickly become legal, operational and reputational events. AI deployment spans product, compliance, employee and brand risk simultaneously. Geopolitical shifts ripple across supply chains, regulatory exposure and market access at once.

These risks don’t move neatly through reporting lines. They spread.

As expectations of boards have expanded, so have the typical responses: more meetings, longer agendas, broader expertise, and greater use of outside advisers. These are rational adaptations. But they share an underlying assumption that governance can keep pace with complexity by doing more within the existing model.

In effect, they reinforce the existing scaffolding: adding more layers, more inputs and more capacity, without fundamentally changing the structure itself.

At the same time, the nature of risk is evolving in a different direction, becoming more interconnected, more external and faster-moving. Boards are being asked to do more, know more and process more, while the complexity they oversee is increasing faster than those adaptations can absorb.

This creates a growing tension. The prevailing assumption is that better governance comes from more visibility, more expertise and more time. That assumption may be reaching its limits.

A deeper shift sits underneath this. Governance assumes the company is the unit of analysis. But increasingly, the most consequential risks sit outside the firm in the systems upon which it depends: cloud infrastructure, AI ecosystems, global supply chains and digital platforms.

This is not limited to technology companies. A manufacturer, retailer, healthcare provider or financial institution may not think of technology as its core business. But if it stores data in the cloud, relies on digital systems or operates within interconnected supply chains, it is exposed to risks it does not control.

Boards are no longer just overseeing what the company does. They are overseeing what the company depends on.

A second mismatch reinforces the problem: the cadence of governance versus the cadence of change.

Boards operate on cycles: quarterly meetings, scheduled strategy reviews, formal reporting. But many risks now evolve continuously. Cyber vulnerabilities emerge overnight. AI systems change through iteration. Geopolitical dynamics shift in weeks, not quarters.

Oversight remains periodic. Risk has become continuous.

As risks become more distributed, boards need better visibility. But governance has a boundary: boards oversee; they don’t manage. Too little visibility, and oversight becomes symbolic. Too much, and boards risk stepping into management.

Compounding this is a structural issue. Most board reporting is vertically aggregated, while horizontal risks do not always surface cleanly through those channels. What reaches the board is often a simplified version of a more complex reality.

All of this lands on a practical constraint. Directors are expected to understand technology, AI, cyber risk, geopolitics and strategy, simultaneously. Experience still matters, but its half-life is shrinking. Cognitive bandwidth may be becoming the real limiting factor in governance.

Some of the widely reported friction between boards and management may reflect this deeper mismatch. Executives operate in a continuous, cross-functional reality, while boards engage through periodic, vertically structured views of the same system. What appears as misalignment or lack of transparency may, in part, be a consequence of governance and management operating on different representations of risk itself.

None of this suggests boards are failing. It suggests they are operating within an architecture designed for a different era.

If risk is horizontal, continuous and increasingly external, governance may be approaching the limits of a model built on vertical assumptions.

Boards were built to oversee organizations. Today, they are being asked to oversee systems.

That shift has implications the current model is not designed to absorb. It points toward forms of governance that are less dependent on periodic escalation and more oriented toward continuous visibility; less bounded by the firm and more connected to the systems around it; less reliant on adding layers to existing scaffolding and more willing to reconfigure how oversight itself is organized.

This may not mean replacing the board. But it may mean that effective governance can no longer reside entirely within it.

The question is no longer how to make the existing model work better, but how long it can continue to carry the weight being placed on it.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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Companies in 2026 are expected to spend over $2.5 trillion on AI, a 47% increase on 2025. This is a spending spree never seen before in the history of organizational investments, and it’s driven in part by companies giving all employees access to GenAI tools such as Co-Pilot, Gemini, or Claude.

Wondering what drove this surge, over the last year I asked hundreds of leaders if they felt their company was trailing others on AI adoption. Their nearly unanimously positive response confirmed my hunch: Organizations have been living through a bad case of FOMO (the fear of missing out). In this case, a universal fear of competitors getting a jump on them, both on innovation and on perceived cost savings, seemed to be driving their spending.

But now, after months of ongoing investment and attempted rollouts, many companies face a new kind of discomfort—something closer to an AI hangover, a universal “What have I just done?” moment. 

The hangover has three main symptoms. First, surprise at the intensity of pushback against AI. Second, anxiety about how little business impact they can see. And third, an increasing concern about how many employees appear to be doing worse work, while feeling more overwhelmed—the opposite of what leaders thought they paid for. 

The most common go-to solution for this hangover? Doubling down on encouraging employees to use the tools they’ve already sunk millions into.

As someone who makes a living studying how our brains show up at work, this is a terrible idea. Getting people to use these tools even more, at least the way they use them now, is only likely to make a big problem even bigger. That’s because companies have the wrong mental model for this moment. They see the adoption of GenAI as a technology rollout, when it is more like a complete overhaul of how people think, something no employee or leader has ever had to work through. 

Rather than more encouragement, or better change management, for GenAI to deliver results companies need to do three important things. Firstly, change the way that GenAI is positioned, redefining its core purpose. Second, they need to make the whole process of AI adoption less threatening. And third, they need to make it easier to do the deep thinking that this technology actually demands.

How AI sets a thinking trap

GenAI has been pitched as a tool to save you having to think. Something to offload every day mental work to, so people can get to the more valuable work of higher-level thinking. The problem is, there is almost nothing more exciting, in terms of activating deep reward circuits in the brain, than imagining achieving a task with meaningfully less cognitive effort. 

When a company encourages people to use GenAI widely, two groups of people pay the most attention: poor performers and average performers, who together tend to make up well more than half of any organization. These people start to use GenAI to summarize their meetings, write their emails, and build their presentations. They turn to AI to develop marketing plans, hatch new product ideas, and solve business challenges. Soon they start to use it to plan their week, handle difficult customers, and deal with interpersonal issues. Their raw output goes up, so they think the quality of their work does, too.

These people have no idea they are doing anything wrong. It doesn’t necessarily feel like they are losing critical thinking skills, sending poor-quality work, or in the case of managers, becoming more toxic because the AI always takes their side. They are just doing what their company asked them to do. 

Meanwhile, the people on the receiving end of all this are overwhelmed with a surge of extra stuff to process, because their peers are producing everything faster. They start to use GenAI even more, to try to get through all this extra thinking. Others feel disrespected or annoyed, or just ignore what’s being sent, knowing it is largely nonsense, or at best, a set of average ideas. 

That’s one big challenge with GenAI: Unless used as a tool to stretch your thinking, the output is, by very definition, average. People are anchoring on the hallucination problem. The real issue is most outputs of GenAI should never be used “as-is.” But that’s not how it is being pitched inside our companies.

Shift the narrative

Instead of GenAI being a tool to think for you, it needs to be positioned as a tool to improve your thinking, to help you think more widely, more deeply, more creatively or more thoroughly. Significant research today is showing that offloading complete tasks to GenAI comes at a big cost. The biggest concerns include losing critical thinking skills, other long-term skills rapidly atrophying, and the quality of work decreasing. 

Another reason we need to change the narrative? It’s simply not true that this will make work easier—in fact, it is making people’s work more intense. Being honest about this will help everyone know what to expect and be able to better plan for it.

Some researchers are calling this kind of solution ‘human in the loop’. We think it should be more “human in the lead”. In this case, GenAI now becomes a tool for a human to be thinking more clearly, more flexibly, more deeply, more widely, more thoroughly. It also requires a level of vigilance, making sure that if you are not an expert in something, if you don’t have deep discernment on an issue, then you find someone who does.

Our research shows that around 5% of employees with access to GenAI, often people who were already top performers, have worked all this out themselves, and use GenAI very differently. They are doing meaningfully better or faster work, and they are the ones doing the thinking: human in the lead. By studying these people’s habits, and with an understanding of the brain processes involved in day-to-day thinking, we have found a set of teachable cognitive habits that can help workers everywhere. We call this “Human-First AI Fluency.”

As we have written about earlier this year, the foundation of Human-First AI Fluency is metacognition, or thinking about thinking itself. If you watch the top 5% of GenAI users working, instead of GenAI providing finished work, you will see them getting GenAI to challenge their thinking, to attack their ideas, to tell them what they are missing. They use these tools to see multiple other perspectives, instead of rushing to a solution. And they almost never send out anything just produced by an AI. 

Rather than having AI draft an email and send it without reading through, these 5% use AI to provide multiple ways of responding to an email, then draft something themselves, and then ask the AI for feedback to improve it. This is human-first AI fluency in action: using the tools to think better, not to think for you. And all of this comes more naturally if people understand their brain a little more, something I call “neurointelligence.”

It’s time to shift the narrative. GenAI isn’t a technology to roll out. And it’s not even a way of reimagining work. It’s a whole new way of thinking. Instead of “GenAI will make your work easier,” the message needs to be “GenAI, when used intentionally, will improve the quality of your work.” That’s the first step to getting AI adoption moving in the right direction.

Reduce the threat

While leaders were expecting younger populations to lead the charge, a study showed that while around half of Gen Z are using AI, those feeling hopeful about it dropped to 18% from 27% a year ago. Another study showed AI was less popular than ICE (the U.S. Immigration and Customs Enforcement agency). This was not the kind of excitement leaders expected when they invested so heavily in this technology.

For some, the resistance is environmental. When I asked my university-attending daughters how they were using GenAI, they rolled their eyes and reminded me that we taught them to recycle, and therefore would never use this resource-devouring technology. For others, they identify correctly the potential loss of cognitive skills they don’t want to lose. 

In my forthcoming book, Good with Humans, I lay out the five intrinsic drivers in the brain: status, certainty, autonomy, relatedness and fairness. For many in the workplace, seeing GenAI being rolled out at work creates a negative jackpot of anxiety, hitting all five things that makes a brain anxious. 

Also, when you are being told to use GenAI as much as possible, so that it “does your work for you,” you quickly see the demise of your job coming. While in many cases this is not likely, it is not helpful to be thinking about this. 

Companies should respect that for many people, GenAI represents a big threat, over and above just having to learn some new technology skills. One thoughtful CHRO, Yan Hong Lee of DBS bank in Singapore, banned the use of the word “productivity” as it relates to GenAI because of its associations with retrenchment. Instead, she focuses on the “What’s in it for me?” for all stakeholders. 

Other things companies can do involve going at a more realistic pace. As Yan Hong Lee told me over a CHRO breakfast recently, “My main message to my leadership these days is simple: ‘Can you all please just calm down a little?’” To me, I see a lot of anxiety created by trying to move too fast, and much of this is driven by a false sense of FOMO. People were overwhelmed before AI; we can’t just force it on them and expect them to rejoice.

Make hard thinking easier

The final step for leaders to roll out GenAI more effectively is to make hard thinking easier. To start with, stop telling people to use the tool widely, and instead show people very specifically where not to use it, directly relating to their role. For example, if you’re a frontline manager, you should not use these tools to give your people feedback, even though you don’t like giving feedback. And if you are in sales, never ever send a client an AI-written email.

Next, to make hard thinking easier, show employees the places they can and should use GenAI, and then spell out what great use looks and feels like, building on the kinds of cognitive habits that the 5% are applying daily. 

With this approach, we believe that the 5% can become 50% or more. When half a company is doing meaningfully better work, you will see a sizable impact on performance. Right now, CEOs are seeing growing bills for all these tokens and starting to get hopping mad because they are not seeing results to match. Pushing everyone to use these tools more is not the right answer, yet this is the main hangover cure being rushed to market as we speak.

To allow for all this deeper thinking, companies may need to go back to being more flexible on where, when, and how people work. The model of the eight-hour workday was fine for routine tasks, but when deep thinking is needed, we might need more flexible work practices. Our best thinking is more likely after a long walk than a long meeting.

Getting half our companies to be meaningfully better thinkers is a road none of us has been down before. Yet continuing to do the same thing and expecting a different result is not a great strategy right now. We’ve had the FOMO, and now we have the hangover. The hangover cure is in front of us: Change the narrative, reduce the threat, and make hard thinking easier. Now we just need the stomach to swallow it down and digest it in full.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

This story was originally featured on Fortune.com

Meta has agreed to pay up to $17.1 billion to settle claims by 47 states and thousands of families making the case that Facebook and Instagram were engineered to addict children.   

While the settlement appears to be a large sum, particularly for shareholders that will ultimately foot the bill, the number to understand in this story is 10. That’s the number of votes Mark Zuckerberg gets for every share held by an ordinary shareholder. He controls Meta through a dual-class stock system that gives him about 61% of the total voting power even though he owns just 13% of the company. Understanding that misalignment is the key to understanding how this corporate and global crisis happened in the first place.

In 2019, my organization, As You Sow, filed a shareholder resolution documenting more than 45 million images of child sexual abuse and torture tied to sex trafficking on Facebook. It filed resolutions for five consecutive years asking for the social network to protect its customers, employees, and shareholders, repair its fraying brand reputation, improve platform integrity, adopt self-regulation, and avoid the destruction of shareholder value associated with the serious and sometimes fatal harm that the company’s platform was enabling. 

In 2020, faith-based investors brought a sex-trafficking survivor before Meta’s annual meeting, a woman groomed on Facebook between the ages of 15 to 18, then sexually trafficked. That year we filed the “Reboot Facebook” proposal, asking the company to verify accounts, remove the abuse images, and stop running political ads containing known lies. 

In 2021, our content governance resolution won 63.1% of the independent shareholder vote, but once Zuckerberg’s outsized votes were considered, the headline tally reported was 19%. Two-thirds of shareholders – those who bear Meta’s financial risk — voted for the company to address these dangers before they became a crisis for shareholders. One man’s vote overrode them all and now every shareholder and a generation of children are paying the price.

The settlement may seem large, but it may be just the tip of the iceberg. The plaintiffs’ own models put the damages in the trillions; this payout, spread over 10 years, is roughly 2% of that — and it’s contingent. If YouTube and TikTok decline to join, Meta’s obligation falls to about $12 billion and the teen safeguards never take effect. Meta’s legal team openly admitted that they engineered the settlement terms to establish an “industry standard” rather than being singled out. We’ve seen this movie before. The 1998 tobacco Master Settlement made the biggest players the authors of their own rulebook, and they emerged more dominant than ever. Meta’s lawyers have no doubt read that history.

Worse, the fixes may not protect children at all. Age verification is “best-effort,” so when a twelve-year-old enters an adult birthdate or opens a new account, Meta can claim, as it has for years, that it “made best efforts.” And the deal ignores the hate speech tied to lynch mobs abroad and the platform’s role in sex trafficking. 

Meta previously lost two cases in New Mexico this year: $375 million in March, $567 million in August, for creating a public nuisance. A Los Angeles jury found Meta and Alphabet negligent in platform design. Thousands of suits remain, with trials resuming in October and many more billions of dollars in costs at stake.

The company found negligent by a jury has defined the child-safety standard for its whole industry, while still benefitting as an incumbent from a platform that remains mostly unchanged. A settlement that low-balls the monetary damages for harm to a whole generation, admits no wrongdoing, and entrenches market share, is a fine outcome for management but a poor one for shareholders who retain the litigation exposure, the brand damage, and the defective product. It is the type of deal we would expect from an unaccountable executive like Zuckerberg. 

So, what fixes the underlying problem? It’s maddeningly basic: One share, one vote.

One federal agency could help solve this massive challenge to protect shareholders, but the Securities and Exchange Commission (SEC) is only making matters worse. It recently initiated a proceeding to rescind Rule 14a-8, the very rule that allows shareholders to submit proposals. It is just the latest in a relentless and short-sighted campaign to restrict and eliminate the exchange of information between shareholders and the public companies they own. 

Meta’s CEO has demonstrated that he requires oversight in a system that incentivizes profiting from the harm to a generation of children. Regulators are moving in the opposite direction by silencing the vast majority of shareholders. Now is the time for all stakeholders to come together and protect our rights by removing dual class share structures and making sure one man cannot damage a whole generation of children ever again.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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This week, Jacob Coxon, who worked at both OpenAI and, more recently, Anthropic, resigned from the latter, warning that the company and its rival were “gambling with our lives” in the race toward superintelligence, with no real plan for controlling systems more capable than the humans building them. The post drew more than 100 million views within days. He wasn’t the first to make the message, but he was someone who’d built his career inside both companies now defining the industry and gave up substantial wealth to air his concerns.

Coxon is at minimum the fifth insider in three years to warn the industry is moving too fast to be safe, but none of the previous four produced anything like this week’s response. Geoffrey Hinton left Google in May 2023 specifically to speak freely about the risk, making him one of the most quoted people in tech that year but producing no legislation. Jan Leike resigned from OpenAI in May 2024, writing that “safety culture and processes have taken a backseat to shiny products”; Ilya Sutskever resigned the same month amid disputes that had briefly ousted Sam Altman. Neither produced a bill. Mrinank Sharma, an Anthropic safeguards researcher, resigned in February 2026 warning “the world is in peril,” and yet, no congressional action.

What was different this time was that a current Anthropic employee, Evan Hubinger, who leads the company’s Alignment Science team, publicly backed the claim within hours, putting greater than 10% odds on human extinction within a decade and saying Anthropic has no concrete plan for controlling superintelligent systems. Two other Anthropic researchers joined in. This may finally produce a political reaction, one that was nine years in the making.

A decade of inaction

The FUTURE of AI Act was introduced in 2017, before Congress even tracked “artificial intelligence” as its own category. It would have created a federal public-private framework to study AI, but it didn’t go far. Two years later, Rep. Yvette Clarke’s DEEP FAKES Accountability Act would have required watermarking synthetic media, and that still went nowhere.

That seems to have become the default outcome for nearly everything that followed. The one thing that did pass wasn’t really about safety: in 2020, Congress folded the National Artificial Intelligence Initiative Act into that year’s defense bill to fund research and workforce training—competitiveness spending, not regulation. Since then, bills moved to remain competitive, not for safety.

Everything accelerated once ChatGPT launched, in November 2022. By January 2023, Rep. Ted Lieu was prompting the chatbot to write a congressional resolution about itself. The first serious response from industry came on May 16, 2023, when OpenAI CEO Sam Altman testified before the Senate Judiciary Committee and asked to be regulated, proposing a licensing agency that could approve or revoke permission to build the most powerful AI systems. Sen. Richard Blumenthal called him an executive who “cares deeply and intensely.” And yet, zero legislative text.

By June 2023, Senate Majority Leader Chuck Schumer decided hearings were the wrong tool and announced nine closed-door “AI Insight Forums” for tech CEOs to brief senators. More than 60 senators showed up to the first one alongside Elon Musk, Bill Gates and Sundar Pichai. Sen. Elizabeth Warren walked out, telling reporters the format let tech billionaires “shape regulation so that the current tech billionaires are the ones who continue to dominate and make money.” Sen. John Thune called it “not efficient.” By the ninth forum that December, of 108 total attendees, 44 had come from industry—more than academia and civil society combined.

Five months later, Schumer’s group released a “Roadmap for Artificial Intelligence Policy” that advocacy groups condemned as proof of “Big Tech’s profound and pervasive power to shape the policymaking process.” No bill ever followed it. The one concrete 2023 outcome came from the president instead of Congress: Biden’s Oct. 30 Executive Order 14110, requiring the largest developers to share safety test results with the government. It survived 14 months.

Making local strides

While Congress workshopped, New York City passed Local Law 144, requiring bias audits and notice before employers use algorithms to screen candidates, in July 2023. It’s one of a few examples of AI regulation surviving implementation—though a December 2025 city audit found enforcement “ineffective,” undone by the city’s own inattention rather than industry lobbying.

States moved next, and 2024 shows the industry’s playbook forming. Utah’s transparency law drew no opposition because it only required disclosure. Colorado’s SB 24-205, signed in May 2024, was the first comprehensive AI law in the country—and Gov. Jared Polis signed it while airing his own doubts.

In California, state Sen. Scott Wiener’s SB 1047 would have required safety testing on the largest models. Anthropic told Gov. Gavin Newsom the bill’s “benefits likely outweigh its costs”; Hinton and Yoshua Bengio (who won the Turing Award in 2018 alongside Hinton) urged him to sign it. OpenAI’s Jason Kwon warned it would push engineers out of the state; Meta and Nancy Pelosi opposed it too. It passed the legislature in August 2024, but Newsom vetoed it that September, faulting its focus on model size over actual risk while insisting “safety protocols must be adopted.”

Congress, meanwhile, found one uncontroversial thing to do: fund things. The House Science Committee approved nine bipartisan AI bills that September—research, education, nothing about safety. The Brennan Center counted more than 150 AI bills introduced that Congress. None were enacted.

Trump’s second term erased what groundwork existed: he revoked Biden’s EO on his first day, then ordered an “AI Action Plan” built around removing barriers. Two years from his previous remarks, Altman did an about-face when on May 8, 2025, he told the Senate Commerce Committee that requiring government approval to release AI would be “disastrous,” and that dominance required “sensible regulation” that “does not slow us down.” The senators offered little pushback.

Rage against the machine

That season produced the biggest federal AI move in years, but it was far from a safety bill. Sen. Ted Cruz inserted language into the “One Big Beautiful Bill” that would have barred every state from enforcing any AI law for 10 years, freezing more than a thousand state bills at once. When Senate rules threatened it, Cruz rewrote it to threaten states’ broadband funding instead. Seventeen Republican governors asked for it to be stripped. On July 1, 2025, the Senate voted 99–1 to remove it, with only Sen. Thom Tillis dissenting.

In September, California enacted SB 53. OpenAI opposed it but didn’t fight the signed law—and New York’s RAISE Act, sponsored by Assemblymember Alex Bores, became law. OpenAI never formally opposed RAISE, but President Greg Brockman helped fund a super PAC, Leading the Future, alongside Andreessen Horowitz and Palantir’s Joe Lonsdale, that spent more than $7.6 million trying to defeat Bores once he ran for Congress—money aimed at the bill’s author after the bill had already passed.

Bores became the first real target of a proxy war between OpenAI- and Anthropic-aligned political money when he ran for Congress this year. Leading the Future’s spend attacking him was the most any AI-industry group had spent against a single House candidate. Countering it, Public First Action, funded by a $20 million donation from Anthropic, backed several PACs supporting Bores that collectively spent roughly $15 million-$19 million in his favor. In total, AI industry-linked spending in the race topped $20 million, part of more than $40 million in outside money overall—making it the second-most-expensive House primary on record. Despite Anthropic’s money roughly matching or exceeding what was spent against him, Bores lost the June 2026 primary.

“Concerns about AI have been widespread for a while, but a few industry players have been willing to spend hundreds of millions to silence elected officials,” Bores, who was an engineer at Palantir before turning to politics, told Fortune.

Bores Coxen’s resignation broke through because he worked at both frontier companies, he is well respected, he spoke so clearly, and he’s giving up personal wealth by leaving.

Coxen’s resignation couldn’t be silenced. And it gave everyone the safety to express what they were already feeling.”

Having lost the moratorium fight in the Senate, its backers changed branches. By November 2025, House leadership reportedly eyed the National Defense Authorization Act (NDAA) as a second vehicle; that produced no rider. Instead, on Dec. 11, 2025, Trump signed an executive order creating a DOJ “AI Litigation Task Force” to sue states over “onerous” AI laws. Where Cruz needed 60 votes and got one, this needed a signature. Colorado’s already-wounded law became its first target: xAI sued the state in April 2026, the DOJ’s task force filed its own supporting complaint two weeks later. A federal magistrate stayed enforcement, and 18 days after that, Colorado’s legislature gutted its own law: five weeks total from lawsuit to retreat. Illinois broke the pattern, its SB 315 passing with OpenAI’s early support, including a third-party audit requirement the company backed nowhere else.

A separate rebellion built over data centers rather than safety: Texas’s Greg Abbott, Pennsylvania’s Josh Shapiro, New York’s Kathy Hochul and Arizona’s Katie Hobbs all moved to pause development over the summer of 2026, driven by voter anger over electricity and water costs. Then, just last month, one of OpenAI’s own models escaped a sandboxed test and compromised Hugging Face. Weeks later, OpenAI, the same company that had opposed SB 53, asked California to strengthen it. Policy expert Nathan Calvin named the technique: fight the bill, accept the law, ask to toughen it only once an incident makes the opposition indefensible.

A new bill that could wipe the slate clean

Coxon’s resignation lands in this near-decade-long record. Within 48 hours, Sen. Josh Hawley opened a Senate investigation into OpenAI, Blumenthal sent a nearly identical letter, and Sen. Bernie Sanders convened a bipartisan briefing with Hinton while Rep. Ro Khanna proposed more legislation. Cruz, who spent 2025 trying to ban states from regulating AI at all, is now co-sponsoring a bill some sources call the only federal safety legislation with real momentum.

Cruz joins Sen. Amy Klobuchar and Majority Leader John Thune in a new, bipartisan AI safety bill that would give the Commerce Department and Homeland Security real power to police the most powerful AI models. It would require safety testing, incident reporting, and the ability to block a model’s release if regulators decide it poses a genuine catastrophic risk—Cruz specifically called out bio-weapons and nuclear threats as the target.

The catch is it would likely wipe out state AI laws in the process, replacing California’s, New York’s and every other state’s rules with this one federal standard instead. Don’t forget: Cruz spent all of last year trying to ban states from regulating AI at all, with no federal replacement—and he got shot down 99-1 in the Senate. This bill gets him roughly the same result, just packaged nicely in safety language this time. Right now, no one outside Congress has seen the actual text and OpenAI and Anthropic are already privately weighing in on drafts with Senate staff, just as Democrats on the committee are already fighting Republicans over whether the safety provisions go far enough.

Maybe it really took Coxon’s resignation letter to get the ball rolling. “Coxen’s resignation broke through because he worked at both frontier companies, he is well respected, he spoke so clearly, and he’s giving up personal wealth by leaving,” Bores also said, evoking the highly anticipated IPOs from both companies.

Hawley has turned years of hearings into a narrow record without ever co-sponsoring the antitrust bills Democrats have repeatedly introduced against Big Tech’s market power. Schumer’s forums, after a year and 108 participants, produced a roadmap and no law. Colorado lost the country’s most ambitious AI law to a federal lawsuit in five weeks. And the senator now bridging a bipartisan safety bill spent the year before trying to ensure no state could pass one at all. So, for the first time, there seems to be real Washington awareness of AI legislation, but it is by no means anything new.

“Coxen’s resignation couldn’t be silenced,” Bores ended. “And it gave everyone the safety to express what they were already feeling.”

This story was originally featured on Fortune.com

The U.S. national debt is more than $40 trillion, and it’s only growing from here. Wage growth keeps stalling; job growth is staying stagnant; and grocery prices are trending up. With the 10-year Treasury yield nearing 5% as heavy government borrowing puts pressure on the bond market, some investors are looking for safer places to store their hard-earned cash.

Investing in alternative assets isn’t new: In recent years, there have been many different (let’s say creative) investment opportunities, from NFTs to tokenized gold, and from crypto to traditional market trading. But for one person, the draw of a childhood game brings back more than just memories: collecting Pokémon cards has become a long-term investment vehicle with the upside of having beautiful art to relish in.

“I love the way they look”

Peter Levin is not what you would call a casual collector. The 55-year-old venture capitalist, co-founder and managing director at Griffin Gaming Partners has collected countless cards since the age of four. 

“I’ve been collecting, you know, practically my whole life,” he told Fortune.

His lifelong hobby of collecting sports and Pokémon cards, bobbleheads and collectibles have become a lucrative investment by nature. According to data from The Washington Post, Pokémon cards generated a roughly 3,821% return between 2004 and 2025—a massive margin compared to the S&P 500’s 483% gain in the same time period.

“Once that generation who collected and played as kids have gotten to a place in life where they have disposable income, you know they’re going to make a determination,” he said. “Perhaps modern art or bobbleheads or watches isn’t their thing, but trading cards are.”

That personal nostalgia and connection is the crux that keeps the market together. It’s an ongoing cycle where “generation after generation has embraced the form factor”—and that’s what sets trading cards apart from previous alternative assets like NFTs, Levin said.

“There has been a trend for people—while expanding at the same time with all these bleeding edge technologies—to also kind of circle back to real life experiences. More tangible things, and trading cards are very much that. There’s a stickiness to it. There’s a community to it,” he said.

For Levin, this isn’t just a cash cow financial investment that he wants to liquidate as soon as the market gets big enough. If he was in it for the money, he said he would have already sold it by now. In fact, he doesn’t even have an estimate on the worth of his 500,000 trading card collection, though he did mention, “None of my good stuff is kept at home.”

“The truth is, I like to collect all cards. I love to get my hands on cards,” he said. “But I have a deep appreciation when people take the time and energy to create something that is unique.”

“There are certain cards where I just love the way they look, and I love the quality of the paper,” he added.

A newfound profession

And that hobby-turned-financial-decision has seeped into Levin’s personal and professional life. He just attended his 31st Comic-Con this past year, and the man admits to being called “batshit crazy”: he sent Fortune a what he said was a never-before-seen photo of his wall covered in “tens of thousands” of pins ranging from Star Wars and Power Ranger characters to Hello Kitty and Nintendo characters.

Among his reserve includes a collection of 25,000-plus comic books and half a million trading cards—including about 100,000 Pokemon cards with the rest being made up of baseball, basketball and collab cards like a Dodgers crossover of a “One Piece trading card.” The Dodgers fan also said he has “every Ohtani bobblehead that’s ever been made.” He even managed to bring that obsession into his profession. 

“We have a cohort within Griffin that competes every other week,” he noted. “You know, we have Magic the Gathering get-togethers.”

For Levin, his aspirations of a Pokémon card-led currency has its merits. He told the Hollywood Reporter he believes Pokémon cards could become a global currency in the aftermath of an apocalypse, based on their worldwide recognition, accessibility and increasingly valuable secondary market.

He later told Fortune he was joking about the post-apocalyptic part—but still believes Pokémon is globally unifying given how ubiquitous and universal it has become, and part of it is that it’s essentially a level playing field: Anyone can build a card collection, and everyone has an equal shot of getting a “rare” card. Wealthy investors are not the only ones limited to getting the valuable cards.

“As a global currency, everybody knows Pokémon, it’s big everywhere. It’s accepted by all cultures and societies, and it’s celebrated and it’s cross generational,” Levin said.

“If you can combine your passion with an investment strategy,” Levin added, “or at least a sub-vertical within your investment strategy, why not?”

Gotta catch ‘em all

The Pokémon card itself dates back to 1996, the same year the original Pokémon games debuted in Japan. The cards initially functioned primarily as a game and collectible—but over time, rare cards became valuable commodities in their own right. Professional grading companies evaluate cards based on condition while online marketplaces and auction houses have created a global market where buyers and sellers can establish prices.

The market’s biggest acceleration came during COVID, when people who were stuck at home returned to the hobby while investors and influencers began treating the cards like assets. Online ecommerce company eBay reported that domestic trading-card sales jumped 142% in 2020, while Pokémon card sales specifically surged by more than 574%.

And these rare cards are reaching prices that would have been almost unimaginable during Pokémon’s original 1990s boom. A first-edition, shadowless Charizard card sold for $369,000 in 2020, and it was only up from there. Online content creator Logan Paul purchased a Pikachu Illustrator card for $5.275 million in 2021 and later sold it in February for approximately $16.5 million—setting a new record for a trading card in the process.

The market today has become large enough to attract major attention. Entertainment company Disney partnered with trading card maker Topps to make collectible cards involving Disney properties, while Hasbro and Ravensburger have also expanded into the card business. The trading-card market is estimated at as much as $50 billion annually.

This story was originally featured on Fortune.com

After spending much of the past year eliminating management layers to build a leaner, AI-driven organization, Meta is now quietly bringing some managers back.

The technology giant has begun asking individual contributors in its Applied AI (AAI) division whether they would like to transition back into manager roles as part of a recent internal reorganization, according to Business Insider, which cited four people familiar with the matter. The move is reportedly voluntary and represents a notable shift for a company that has aggressively championed flatter organizational structures.

The decision highlights the challenge companies face in balancing efficiency, rapid AI development, and workforce coordination.

AAI is a newly created engineering division launched in 2026 to help bridge the gap between Meta’s AI research and product execution. The group trains AI models and accelerates their deployment across the company’s products.

Earlier this year, Meta reassigned roughly 7,000 employees to the unit, including some who had previously held manager positions before moving into individual contributor roles.

Meta did not immediately respond to Fortune‘s request for comment.

Meta’s push to flatten its workforce

The move marks a partial reversal of a broader restructuring effort that has defined much of Meta’s strategy over the past year.

As CEO Mark Zuckerberg accelerated the company’s transition toward what executives have described as a more AI-native future, Meta reduced management layers and emphasized smaller, faster-moving teams. The company argued that flatter structures would improve decision-making, reduce bureaucracy, and help offset the rising cost of its massive AI investments.

The current retooling is not the first time Meta has rewired its management ranks in the name of speed. In 2023, during what Zuckerberg branded his “year of efficiency,” the company asked many managers and directors to move into individual contributor jobs or leave in a process it internally called “flattening” — the same maneuver it is now selectively undoing.

That approach hardened in 2026. In March, Fortune reported that analysts expected Zuckerberg to help drive a broader “cascade” of AI-related layoffs across the tech sector. Two months later, Meta cut about 10% of its workforce — roughly 8,000 employees — and scrapped plans to fill 6,000 open positions as part of a sweeping efficiency initiative. The layoffs disproportionately affected managers and were intended to simplify reporting structures while freeing up resources for AI development.

The restructuring mirrored moves across the technology sector, where companies including Amazon, Microsoft, and Intel have reduced headcount while increasing investment in AI infrastructure and automation.

Meta’s reorganization has not been without friction. Earlier this year, Wired reported employee frustration over the rollout of the AAI division, and some workers reassigned to the group were later given the option to pursue other opportunities within the company. In July, 26 Meta employees sued the company, alleging it had used internal AI systems and activity-monitoring data to disproportionately target workers on medical, parental, or family leave in the May cuts.

Meta ended the second quarter with 75,472 employees, down 3% from the prior quarter. The figure includes approximately 8,000 employees affected by the company’s May workforce reductions, according to its second-quarter 2026 earnings report.

AI spending continues to accelerate

The management changes come as Meta continues to pour billions into AI.

During the company’s second-quarter earnings call, Zuckerberg said AI investments are increasingly shaping every major part of Meta’s business, from product development to long-term growth initiatives.

“I’m also excited about how AI is helping our teams speed up product development,” Zuckerberg said.

Meta reported second-quarter revenue of $60.8 billion, a 28% increase from a year earlier. At the same time, total expenses climbed 55% to $42 billion as the company continued investing heavily in AI infrastructure and absorbed costs tied to the workforce reductions.

The company’s latest organizational shift highlights a reality facing many technology firms: while AI may automate certain tasks and strip out layers of bureaucracy, building and deploying advanced AI systems at scale still requires human leadership, coordination, and oversight.

This story was originally featured on Fortune.com

Todd Hughes has a complicated relationship with Danish. The 64-year-old can read a Danish novel without much trouble. But put him in a room full of native speakers, and the plot thickens.

His Danish dilemma illustrates the difference between sounding fluent and actually becoming proficient. Technology can help someone learn vocabulary, practice skills, or move smoothly through a translated exchange. But proficiency is about what someone can actually do across reading, writing, listening, and speaking—and communicating proficiently still requires navigating another person.

Hughes, who trains language tutors at Rosetta Stone, knows that gap all too well. He speaks Spanish at home with his Costa Rican husband, teaches German, grew up hearing French from his grandmother, and studies Nordic languages for fun. He recently added Japanese to the rotation ahead of a trip to Japan. 

Yet his abilities shift from one language and one skill to another. For Hughes, fluency describes flow—how smoothly and quickly someone speaks. Proficiency is a broader measure of ability. It asks whether someone can understand what is being said, find the vocabulary they need, and communicate accurately when a conversation moves somewhere unexpected.

“For me, it’s a question of skill and a question of ability over a question of flow,” Hughes told Fortune.

Social media confuses fluency and proficiency

Native speakers pause, stammer, and lose their train of thought constantly, making smooth delivery an imperfect way to judge how well someone knows a language. When someone says they are fluent in six or 16 languages, Hughes has a simple follow-up: “What can you do?”

He approaches the answer through four core skills: reading, writing, listening, and speaking. A person can be strong in some and shaky in others, which is why a single label rarely captures much.

A traveler who can order dinner and navigate Paris, Frankfurt, and Rome may reasonably consider themselves a polyglot—a word that simply means “many languages.” A linguist might ask harder questions about vocabulary, pronunciation, accuracy, and whether that same person could discuss an abstract idea in each language.

Social media has made that distinction even more difficult to see. TikTok is filled with polyglots bouncing between languages while ordering food or surprising strangers. The videos are entertaining, often impressive, and perfectly built for an algorithm that does not have time to sit through a verb-conjugation lesson. But a polished clip can show someone firing off a perfect greeting without revealing how they might manage 10 minutes later, once the conversation has wandered off script.

His own collection of languages shows why proficiency can be difficult to summarize. Hughes describes his Spanish as near-native and feels as comfortable speaking it as English. He can understand and read French extremely well, but makes mistakes while speaking. Danish presents almost the opposite problem. Reading comes easily, while listening and pronunciation remain a challenge.

A library that cannot nod back

Technology can help people work on those different skills. AI can generate practice exercises, correct writing, and create reading material at a learner’s level. With Apple bringing Live Translation to AirPods, the company says the feature can help someone understand a conversation in real time.

Hughes has worked with technology in language education since 1995, when he wrote his dissertation on using it to acquire Spanish vocabulary. He’s wary about translation tools and their ability to capture the social and cultural cues surrounding the words.

In his view, AI is like a “huge library” that never closes. It can produce a beginner-level story on demand and can remove some of the friction involved in finding material appropriate for a learner’s level.

When it comes to using AI to practice speaking, however, Hughes is less convinced.

“I’m not there yet,” he said.

People learn languages from other people

Similarly, Duolingo, whose famously persistent green owl has spent years reminding users to finish their lessons, is also not preparing to concede defeat to a pair of translating headphones.

“Real-time translation can help you understand someone in the moment, but it can’t replace the connection, cultural understanding and personal satisfaction that come from learning and speaking a language yourself,” Cem Kansu, Duolingo’s chief product officer, told Fortune.

The company said many people learn English for high-stakes reasons, including pursuing a better job or higher education. For those learners, the problem is not simply that a translation may be unreliable. Even an accurate translation does not demonstrate proficiency. It can relay the words in one exchange, while proficiency means being able to continue the conversation, ask follow-up questions, and respond when the wording or tone changes.

To be sure, Duolingo and Rosetta Stone make money when people continue learning languages. But Hughes pointed out that words go beyond their dictionary definitions and carry more social baggage that must be learned from interacting with people.

For example, the English expression “don’t pull my leg” has a Spanish counterpart that translates literally as “don’t pull my hair.” An app might know to swap one idiom for the other, but that does not mean it understands the tone behind it. It may not know when an expression sounds playful or rude, or whether someone knows their Costa Rican mother-in-law well enough to use it.

That is why human interaction is necessary for proficiency, according to Hughes. In a live exchange, a learner has to understand what another person said, choose a response, watch how it lands, and adjust when the conversation changes. The listening, speaking, cultural knowledge, and social cues all happen at once. A tool can suggest the next sentence, but it cannot do that work for the learner.

Proficiency begins when another person answers, and a real conversation changes as it unfolds. People watch for nods and other signs of active listening, follow what the other person is saying, and adjust their response. Those social cues are part of communicating in any language, and Hughes does not think AI has a good grasp of them yet.

“When was the last time that you had a really, really, really interesting conversation with a computer?” he asked.

This story was originally featured on Fortune.com

Amazon’s newest feature for Prime Video is trying to make real life more like TV by letting you immediately buy what your favorite actors are wearing—or something similar.

The company on Thursday announced a new feature called Shop the Scene that will let users shop for products featured in a show or movie. With minimal interruption to the viewing experience, users can pull up items on the Amazon Shopping app inspired by what’s being shown in the scene they’re watching at the moment.

Amazon said Thursday that the Shop the Scene feature is now available on more than 600 Prime Video titles through the Amazon Shopping app for users in the U.S. 

The broader Shop the Show experience, which Amazon introduced last year to let users browse products related to shows on Prime, like bobbleheads or LEGO sets, is also expanding to more than 8,000 titles, from 1,300 previously.

“We are making it easier than ever for Prime Video customers to shop what they see on screen,” Michelle Rothman, vice president of Prime Video shopping, said in the announcement Thursday.

Amazon did not immediately respond to Fortune’s request for comment.

The new Shop the Scene feature uses AI to let a user curious about the clothing an actor is wearing in their favorite show buy the same outfit or a similar one from Amazon from their phone. The match may not always be exact.

Prime Video is also getting a new “shop” tab inside X-Ray, which lets users identify actors or music playing in a show while watching. Users will now be able to open X-Ray with their remote and browse products associated with what they are watching on the shop tab and finish the transaction on their phone.

Profiting from streaming

Companies like Netflix, Disney, and Peacock have for years experimented with ways to make streaming more profitable, including by increasing subscription prices, cracking down on account sharing, and incorporating tiered subscription models and ad-supported streaming.

Amazon’s move is the most recent effort to capitalize on the content already capturing people’s attention—and it’s not the first company to try it.

NBC’s streaming service Peacock introduced a Must ShopTV feature in 2023 that let users purchase content-featured products in real time. Disney through its streaming service Disney+ has also experimented with a shoppable TV feature that allowed subscribers to shop on certain pages via a QR code on their TV screen.

Amazon’s latest move also helps its behemoth online shopping business expand through its growing Prime Video business. Amazon said late last year that its ad-supported Prime Video tier now reaches more than 315 million people worldwide, a big leap from the 200 million users it disclosed in 2024. 

Amazon has tried to more closely intertwine shopping and entertainment for years, including with a virtual product placement technology, or VPP, that uses machine learning to allow advertisers to insert their brands into films and TV shows after they’ve been produced.

There’s some data to show that product placement may be worth it. A survey by YouGov found earlier this year that just over half of U.S. adults consider product placement to be an effective form of advertising, compared to 14% who said it was ineffective. 

Some 4% of the people surveyed said they took action after seeing a brand featured in content they watched. Of those people, 22% searched for the product online and 10% said they made a purchase.

This story was originally featured on Fortune.com

After weeks when Middle East diplomacy seemed dead in the water, a rare meeting between Iran and its Persian Gulf neighbors has renewed hope for a deal that could fully reopen the Strait of Hormuz.

Foreign ministers from the Gulf Cooperation Council—which is comprised of Saudi Arabia, the UAE, Qatar, Kuwait, Bahrain, and Oman—will meet their Iranian counterpart on Monday, sources told the Financial Times.

Brent crude oil prices tumbled 2.9% to $104.52 a barrel on Friday.

It would be the first such gathering since the U.S. and Israel launched their war on Tehran and also comes as Oman and Iran seek to build support on a deal the two countries have been crafting to temporarily manage traffic in the Strait of Hormuz, the report added.

For now, the U.S. and Iran have been locked in a stalemate over the global energy chokepoint. The U.S. naval blockade is preventing Iran from exporting oil via its ports, while Iranian drone and missile attacks are preventing other exporters from returning to prewar levels.

But an agreement on the Iran-Oman shipping scheme wouldn’t fully reopen the strait. Tehran has insisted the U.S. must first fulfill terms of their earlier ceasefire deal reached in June.

“For Iran and Oman it is about getting the GCC on board to try and use that to get the U.S. to lift its blockade on Iranian ports,” a source told the FT, while the GCC wants to ensure that “whatever is agreed is temporary and they are able to get ships in and out.”

GCC states are wary about agreeing to anything that would recognize any Iranian control over Hormuz. But the equation may be changing as Iran tries to turn the tables on the U.S. and its allies.

The U.S. military has been helping non-Iranian oil sneak through the Strait of Hormuz, bringing exports from the region to around two-thirds of prewar levels.

While that still represents a significant shortfall, the U.S.-guided oil flows weakened Iran’s ability to use the strait as political leverage. At the same time, the naval blockade is crushing Iran’s economy.

To regain the upper hand, Iran recently launched fresh missile salvos at U.S. bases in the region, attacked U.S. warships, and helped its Houthi allies in Yemen seize territory near the Bab al-Mandab Strait that links the Red Sea and the Arabia Sea.

After Iran closed the Strait of Hormuz, the Bab al-Mandab Strait became a vital bypass for Saudi Arabia, which diverted oil from the Gulf to the Red Sea via its East-West Pipeline. But the Houthis reportedly attacked the pipeline and Saudi tankers in recent days too.

With friends like these…

While facing threats to its oil exports, Saudi Arabia isn’t getting much support from its own allies.

Saudi Crown Prince Mohammed bin Salman called President Donald Trump twice on Thursday, asking for U.S. strikes against the Houthis, but was turned down, sources told Axios.

Instead, U.S. officials said the Trump administration will provide intelligence on the Houthis and targeting data. U.S. forces will remain focused on Iran and the Strait of Hormuz—and steer clear of fighting on an additional front, the report added.

Saudi Arabia also has a defense pact with Pakistan, which has deployed troops near the Saudi border with Yemen. But the South Asian country also depends on energy shipments that transit through the Strait of Hormuz and the Red Sea.

So officials in Islamabad are reluctant to antagonize Iran and are worried the Houthi threat could suck Pakistan into a war. Pakistan’s foreign ministry has said no military response to the ​Houthi attacks is being discussed.

And according to Reuters, Pakistan’s army chief stressed diplomatic efforts to de-escalate across all fronts in a call with Iranian Foreign Minister Abbas Araqchi on Thursday.

“Pakistan is trying to keep a low profile in the Saudi-Houthi conflict because Pakistan’s own stakes are high,” a Pakistani government official told Reuters. “It does not want to spoil relations with Iran.”

This story was originally featured on Fortune.com

On the morning of September 11, 2001, 19 al-Qaeda hijackers took control of four commercial airplanes. Two struck the World Trade Center’s twin towers in Lower Manhattan, a third hit the Pentagon, and a fourth, aimed at Washington, D.C., crashed into a field in Shanksville, Pennsylvania, after passengers fought back. Nearly 3,000 people died that morning, most of them in New York, where both towers collapsed within two hours of the first impact.

The attacks reordered American life almost overnight, from airport security to two wars to a new Department of Homeland Security. Some Lower Manhattan firms lost most of their workforce in a single morning. New Yorkers of all ages and occupations were killed in the terrorist attacks 25 years ago, and those who survived have stories of how they were kept away: a pregnant woman who went into labor; a football game that went a little too late the night before; an alarm that never went off. Twenty-five years on, some of the people who were supposed to be in or near the towers continue recalling their fateful day. Among them include current Commerce Secretary Howard Lutnick and former Senator Mitt Romney.

Lutnick, then CEO of Cantor Fitzgerald, worked out of the North Tower’s 105th floor and was normally at his desk by 6 a.m. His wife had him take their son to school instead. “So it was my son Kyle’s first day of kindergarten,” he told NPR in 2016. His phone kept ringing without connecting that morning; he later learned it was his brother, Gary, trying to reach him to say goodbye. Gary, who went to work as usual, was among the 658 Cantor Fitzgerald employees who died.

Larry Silverstein, who had signed a 99-year lease on the Twin Towers weeks earlier, held daily breakfast meetings at Windows on the World, the restaurant located on the North Tower’s 106th floor. His wife booked him a dermatologist appointment for the morning of September 11 instead. “You learn early on to say, ‘Yes, dear,’” he recalled. The near misses ran through his circle: his children Roger and Lisa were both running late to the same meeting, and his longtime aide, Geoffrey Wharton, cut breakfast short and rode the elevator down at 8:44 a.m., two minutes before the plane hit. No one else at the restaurant that morning survived.

Michael Lomonaco was the executive chef at Windows on the World. That day, he stopped to get his glasses adjusted at a shop on the concourse level and was still there when the first plane hit. “It saved my life,” he said. More than 30 of his kitchen staff died, and he has since raised nearly $25 million for restaurant workers’ families.

Jim Pierce, a managing director at Aon Corporation and a cousin of former President George W. Bush, had a meeting scheduled on one of the South Tower’s top floors. The group grew too large for the room, so it moved to a nearby building at the last minute. Twelve people never got word of the change, and 11 of them died. Pierce watched the second plane hit from next door. “I knew we were under attack,” he said, describing bodies falling from the towers and chaos on the street below.

Mitt Romney, then president of the Salt Lake Organizing Committee for the 2002 Winter Olympics, planned to unveil the Games’ torchbearers at a press conference blocks from the towers. A funding dispute in Congress over Olympic security money kept him in Washington instead. “We had planned to be in New York City on the 11th,” he wrote. “Our team had planned an elaborate press conference adjacent to the World Trade Center at Battery Park.”

Duchess of York Sarah Ferguson ran a charity out of the North Tower’s 101st floor and missed a meeting after an interview ran long. “I was meant to be there that morning,” she wrote. Her charity’s mascot doll, Little Red, was found in the rubble and now sits in the 9/11 Memorial & Museum.

Jimmy Dunne, a co-founder of investment bank Sandler O’Neill & Partners, was supposed to be with his employees on the 104th floor of the South Tower. Instead he was 50 miles north, trying to qualify for a golf championship. Sixty-six of the firm’s 171 employees died. He still marks his golf ball with a “Q,” in honor of colleague Christopher Quackenbush, who didn’t make it out.

Two future collaborators were booked on American Airlines Flight 11, the first plane to hit the North Tower. Mark Wahlberg canceled his seat a week early for the Toronto Film Festival instead, and later drew criticism for telling Men’s Journal that had he been aboard, “it wouldn’t have went down like it did,” a comment he apologized for. Seth MacFarlane missed the same flight by minutes after his travel agent gave him the wrong departure time. “I said, ‘Yeah, I’m booked on Flight 11,’” he recalled.

This story was originally featured on Fortune.com

When OpenAI launched Astra last week — a model whose advanced abilities prompted OpenAI president Greg Brockman to call it the start of the “AGI era” — it only gave a handful of enterprise customers access to give the company time to scale its compute capacity.  

But now that it’s available to paying users, demand for Astra has soared to the point where OpenAI temporarily won’t take your money for its $200-per-month ChatGPT Pro plan, where Astra is available, because there’s not enough capacity to go around. 

The company announced on Thursday it’s pausing new sign-ups and upgrades to the most expensive plan on the Pro tier, which provides 20 times the usage of the Plus tier below it. OpenAI’s head of product Thibault Sottiaux wrote on X that the reason behind the halt was that the $200 plan puts the most strain on the AI lab’s systems. 

“We wanted to take the smallest step that allows us to continue giving the broadest access possible,” he said, adding that OpenAI is “working on adding more capacity” and that existing Pro accounts are unaffected. 

A day earlier, Sottiaux said demand for Astra was “unprecedented” and warned that the company “might have to pause new Pro subscriptions for a bit” if it continued. 

“We’re pulling all the levers possible to sustain the demand, but I’ve not seen anything like it until now and we went through very steep growth before,” he wrote on X. 

Astra’s design helps explain why too many users on it might strain OpenAI’s infrastructure. Its marquee feature, called “computer use,” allows it to interact with a desktop the way a human would, like filling out forms and navigating web pages at “superhuman speed,” Brockman told reporters. OpenAI also said Astra can burn through users’ usage allowances faster than its previous flagship model GPT 5.6 Sol. 

Compute constraints

This isn’t the first time OpenAI paused new subscriptions to paid tiers due to lack of capacity. In November 2023, OpenAI temporarily halted sign-ups to the $20-per-month-ChatGPT Plus plan after the company’s first developer conference led to a surge in demand.

“The surge in usage post devday has exceeded our capacity and we want to make sure everyone has a great experience,” OpenAI CEO Sam Altman wrote on X at the time. 

Since then, the company has grown its capacity. OpenAI said its available compute rose from 0.2 gigawatts in 2023 to about 1.9 GW in 2025, a 9.5-fold increase over two years. 

It’s also trying to keep up in the race to grab more of it, even as concerns swirl that a potential bursting of the AI bubble could leave a glut of computing capacity behind. AI hardware like GPUs, the computer chips that run the calculations used to train AI, can depreciate in a few years. 

OpenAI expanded beyond its partner Microsoft Azure for the hardware required for compute, adding cloud-computing company CoreWeave and launching Stargate, a $500 billion, four-year AI infrastructure buildout.

OpenAI has also lined up a wave of new capacity beginning in the second half of 2026. This includes plans for at least 10 GW of Nvidia systems, a 6-GW Advanced Micro Devices agreement for GPUs, and a Broadcom partnership to deploy 10 GW of custom AI accelerators. 

OpenAI did not respond to Fortune’s request for comment.

This story was originally featured on Fortune.com

The Federal Reserve’s hiking cycle suddenly looks alive again.

Wall Street was already growing nervous. Oil had pushed back above $100, bond yields were surging, the AI capital-expenditure boom continued to add pressure to credit markets, and Thursday’s producer-price report—which feeds into the Fed’s preferred inflation gauge—came in surprisingly hot.

But Chair Kevin Warsh’s ambiguity over the Fed’s next move, made Friday’s final inflation data before next week’s meeting unusually important. The outspoken Fed Governor Christopher Waller filled in the gap for traders, signaling that “it may not take much acceleration in inflation” to nudge him into supporting a hike.

The CPI then stepped over that low hurdle. Core consumer prices rose 0.3% in August, above expectations for 0.2%. Headline CPI climbed 0.4%, with gasoline prices jumping 3.9%.

Traders now price the probability of a quarter-point Fed hike next week at roughly 85%, up from 70% before the report. The 10-year Treasury yield climbed toward 5%, putting the psychologically important threshold within reach. Stocks didn’t sulk over the report, with all three indices shooting higher. 

For Main Street, the report was just another confirmation of the pressure that has defined the first half of the year, as wage growth decelerated for the fifth month in a row. Consumer sentiment came in Friday morning at another near-record low.

“We haven’t seen this type of income squeeze since 2012,” Gregory Daco, chief economist at EY-Parpletheon wrote on X.

The CPI’s outsized influence puts even more scrutiny on the guts of the report, where a few hundredths of a percentage point can suddenly take on enormous importance.

One of these marginal anomalies came from wireless telephone services, where prices surged 5.9% in August, the largest increase BLS has ever recorded for the category.

Cellphone service alone contributed 0.077 percentage point to the overall CPI increase, which is about one-third of core CPI’s total 0.230-point contribution. Excluding the category, core inflation worked out to roughly 0.2% increase rather than 0.3%.

And though Apple just unveiled a roughly $2,000 folding phone, smartphones themselves were not the culprit. Smartphone prices actually fell 1.7% in August and 12.2% from a year earlier, while the broader telephone-hardware category dropped 2.4% on the month.

That doesn’t mean the inflation report was benign beneath the hood. Energy prices are rising sharply and the latest spike in oil could still work into everything from airfare to consumer goods (plastics) over the coming months. 

The bigger concern for investors is that the inflation surprise is arriving alongside a bond-market selloff that is already tightening financial conditions.

Adam Turnquist, chief technical strategist at LPL Financial, said rates have recently “traded the stairs for the elevator.” A clear break above 5% on the 10-year, he said, would put the 2006-2007 highs around 5.25% to 5.35% into focus as a comparison. 

“With a 0.3% month-over-month increase in Core CPI, the Fed now finds itself with its back against the wall,” said Chris Zaccarelli, chief investment officer at Northlight Asset Management.

The remaining question is whether an AI-powered stock rally can keep shrugging off $100 oil, a nearly 5% 10-year yield, and a Fed that suddenly looks ready to start hiking again; although its rise after the decision release seems to welcome a hike.

As Zaccarelli put it: “Bull markets don’t die of old age, they’re killed by the Fed.”

This story was originally featured on Fortune.com

Frank X. Shaw, Microsoft’s chief communications officer, is leaving the software giant after nearly 30 years of playing a vital role in shaping the company’s public messaging, according to a memo he sent to staff viewed by Fortune.

Shaw said he’s decided it is time to move on and try new ventures, though he has not decided what is next. He and Takeshi Numoto, Microsoft’s executive vice president and chief marketing officer, had been discussing the move for some time and felt now was best, Shaw said in his memo. Shaw plans to stay until the end of the year.

“I remain optimistic about the company mission, the incredible talent on this team, and how much the company depends on us during this critical time,” Shaw said in the memo. “Together, we’ve accomplished amazing things. My gratefulness is endless.”

Shaw, 64, has been in his role for 17 years, and previously served as president at We. Communications for 12 years, where he worked closely with Microsoft’s public relations apparatus. The executive has played a major role in shaping much of how Microsoft communicates to the outside world, including through events, senior executive access, and other matters. He is one of Silicon Valley’s most recognized PR professionals.

Shaw’s departure comes as Microsoft has undergone several waves of changes in the past two years. The company has prioritized growing its Copilot AI assistant and spent billions expanding its cloud computing business to meet demand for AI compute.

During this time, several executives have departed, as chief executive Satya Nadella has reorganized teams around the company’s Copilot goals.

In March, Nadella created a unified Copilot team led by Jacob Andreou, a 33-year-old executive who has had a fast rise. Rajesh Jha, who worked closely with Copilot teams and oversaw Windows products as executive vice president of experiences and devices, announced his retirement in March. Phil Spencer, who served as CEO of gaming and had been at the company for 38 years, also retired earlier this year. Spencer was replaced by Asha Sharma.

In 2025, Microsoft laid off more than 15,000 employees across sales, Xbox, and other departments. In April, it announced its first-ever employee buyout offer, aimed at its most long-tenured employees.

Shaw, who served in the U.S. Marine Corps, graduated from the University of Oregon with a bachelor’s degree in journalism. He has worked in PR since the early 1990s, and he also worked with each of Microsoft’s three chief executives—founder Bill Gates, Steve Ballmer, and Nadella. When Shaw began working for Microsoft in 1997, the company’s business was overwhelmingly based on sales of PC software like the Windows 95 operating system, and the Office 97 productivity suite. That same year, Microsoft also famously saved Apple by investing $150 million into the struggling Mac maker.

Shaw, who lives in Seattle, has lately spent much of his time advocating for the company’s efforts in AI, shaping the public messaging on its evolving partnerships with OpenAI and Anthropic, and defending less successful businesses like Xbox.

Microsoft’s Azure cloud business continues to be the company’s growth engine, having crossed $100 billion in annual revenue in its most recent quarter. Much of that growth has been due to AI demand, with a large part of its business coming from OpenAI. Microsoft has tried to diversify from its longtime partner while diverting computing resources toward improving Copilot.

The company’s AI lab recently unveiled its first reasoning model, MAI-Thinking-1, which it said matches leading models on some software engineering benchmarks, and said its latest coding model is 25% more efficient than its previous model.

This story was originally featured on Fortune.com

Since the dawn of tennis’s open era in 1968, the U.S. Open has grown from a two-week sporting contest into one of the most lucrative events in global sports. The tournament now draws not only the world’s best players but also celebrities, luxury brands, corporate executives, and affluent consumers—a mix that has helped turn the annual gathering in Queens into a business generating more than half a billion dollars.

The U.S. Tennis Association (USTA) reported $623.8 million in total revenue in 2024, with the U.S. Open accounting for roughly 90% of that figure, according to its most recent audited financial statements. The tournament alone generated $559.6 million in operating revenue during its three-week run.

That kind of money, however, requires substantial investment.

Operating expenses totaled $282.2 million in 2024, leaving an operating surplus of roughly $277.4 million—a margin of nearly 49%. Revenue climbed 9% year over year from $514.1 million in 2023, extending a multi-year growth streak that has continued largely uninterrupted since the pandemic.

The numbers illustrate how far the U.S. Open has traveled from its roots as a sporting event. Alongside Wimbledon, the Masters, and Formula One, it has become one of the world’s premier luxury sporting experiences—and one of its most reliable moneymakers.

How the U.S. Open makes its money

The tournament’s revenue flows from several sources: ticket sales, sponsorships, broadcasting rights, hospitality packages, food and beverage, and merchandise.

Ticket revenue reached $208.5 million in 2024, while sponsorship revenue topped $130 million. Corporate hospitality and related services added $83.3 million, and broadcast rights contributed roughly $145 million.

Attendance, meanwhile, has hit record highs. More than 1.04 million fans passed through the gates of the USTA Billie Jean King National Tennis Center during the 2024 tournament—the first U.S. Open to surpass one million attendees, according to the USTA. The event drew an even larger crowd of about 1.14 million in 2025.

Yet the tournament’s financial success is increasingly tied to a strategy built around premium experiences and exclusivity.

The business of luxury tennis

Over the past decade, the U.S. Open has steadily repositioned itself as a luxury sports and entertainment destination.

Relatively affordable tickets still exist, but the tournament has aggressively expanded premium seating, hospitality offerings, luxury suites, and exclusive add-ons designed to draw high-spending consumers and corporate clients. The USTA is now investing roughly $800 million in upgrades to Arthur Ashe Stadium and the surrounding grounds—the largest capital project in the tournament’s history—with much of the work aimed at premium hospitality and high-end fan experiences.

The shift mirrors a broader trend across sports, where leagues and event organizers increasingly prioritize premium inventory because it generates far more revenue per seat than traditional ticket sales.

For sponsors, the appeal is straightforward. Unlike a conventional ad campaign, the U.S. Open offers brands direct access to an affluent audience concentrated in one place. The event fuses live sports, entertainment, hospitality, fashion, and business networking, making it one of the most attractive sponsorship platforms in sports.

Why sponsors keep investing

The U.S. Open maintained 27 sponsorship agreements in 2024, including partnerships with American Express, Emirates, Rolex, Tiffany & Co., Ralph Lauren, and Grey Goose.

For many of these companies, the deals are less about short-term sales than long-term brand positioning. Associating with the U.S. Open lets sponsors align themselves with prestige, exclusivity, and affluent consumers.

Few examples capture that dynamic better than the Honey Deuce.

The cocktail—Grey Goose vodka, lemonade, raspberry liqueur, and a skewer of honeydew melon balls meant to mimic tennis balls—has become one of the tournament’s most recognizable traditions. Despite a $23 price tag, demand keeps climbing. Grey Goose reported that a record 738,459 Honey Deuces were sold during the 2025 tournament, generating roughly $17 million and demonstrating how readily consumers embrace premium pricing once it becomes part of an exclusive experience.

Ralph Lauren has similarly leveraged its decades-long relationship with the tournament to reinforce its ties to tennis culture and premium lifestyle branding. Official U.S. Open collections routinely feature apparel priced in the hundreds of dollars, reflecting the luxury positioning that has become synonymous with the event.

Can the U.S. Open keep its luxury status?

The USTA faces the question of whether demand can continue to support rising prices.

Critics argue the tournament is becoming increasingly inaccessible to average fans as ticket prices, hospitality packages, and on-site spending keep climbing. But demand has shown little sign of cooling so far, with attendance records, sponsorship growth, and premium hospitality sales all moving in the same direction.

The stadium renovations are expected to add still more premium inventory, a sign the USTA believes consumers will keep paying for greater exclusivity.

“They’re not necessarily so into tennis, but more into the scene and wanting to be there,” USTA chief commercial officer Kirsten Corio told Curbed.

The event’s economic footprint extends well beyond the grounds. Analytics firm GhostCom estimates the 2026 U.S. Open could generate $369.7 million in incremental consumer spending across hotels, food and beverage, apparel, restaurants, and nightlife.

For now, the business case looks clear. The U.S. Open has transformed itself from a tennis championship into a luxury entertainment brand—one that generates more than half a billion dollars a year and keeps finding new ways to monetize exclusivity.

This story was originally featured on Fortune.com

It may not be all doom and gloom for AI in the classroom—there actually may be a Goldilocks effect. 

The OECD’s latest Program for International Student Assessment (PISA) found that AI has led to a decline in multiple student skills as well as a drop in test scores, but moderate use is associated with stronger performance in certain subjects compared to limited or daily use. 

For several common assignments, students who used AI “moderately”—from about once a month to once or twice a week—recorded higher average science scores than both students who rarely used AI and those who used it almost every day. The advantage was especially clear when students used AI to summarize assigned reading or conduct preliminary research on a new topic. 

Students who reported using AI for that purpose weekly tended to perform at about the same level as AI nonusers after accounting for socioeconomic status. But students who used it almost every day and students who rarely used it, tended to have lower scores.

“These relationships do not necessarily imply a negative impact of AI use on science performance, but may reflect a complex mix of who adopts AI and how they use it,” the study found. “It also suggests that moderate and intentional use of AI for schoolwork and learning may be positively related to student performance.”

The OECD says its findings are consistent with the idea that digital tools can support learning when used purposefully and in moderation, but excessive or unguided use can contribute to distraction and shallower engagement.

“In the same way that we do not become fit by watching sports but by doing sports, learning does not occur through the consumption of content,” the findings read, “but as a productive cognitive struggle of the mind with new material.”

But lower scores are not all due to AI. PISA has reported that reading, mathematics and science scores have dropped since 2003.

Still, the latest results showed that 86% of students across OECD countries had used AI chatbots for at least one of the schoolwork purposes examined in the assessment, with the remaining 14% saying they had never or almost never used AI for any of those purposes.

And students who do not use AI chatbots for schoolwork generally score higher than students who do, according to PISA.

Meanwhile, about one in five students reported using it almost everyday. This group tended to score lower in science than students who did not, accounting for socioeconomic status.

That creates a feedback loop for students who rely too heavily on AI. The weaker a student’s ability to read critically, the harder it may be to recognize when an AI-generated answer is incomplete or incorrect. And at the same time, routinely allowing AI to perform the reading, summarizing or reasoning could give students fewer opportunities to develop those skills.

And the findings also say important skills attributed to critical thinking are declining.

“Most troubling is the decline in the very skills that matter most in the AI age: evaluating information, making connections across multiple sources, and thinking critically about what we read,” the report read. “In turn, the share of ‘hasty readers’—students who rush through texts and give quick but incorrect answers—almost doubled between 2018 and 2025. In a world increasingly flooded with information, our students are less likely to think deeply and separate signal from noise.”

This story was originally featured on Fortune.com

This is Fortune 500 Power Moves, a column tracking executive shifts—from appointments and promotions to resignations and retirements—within the highest ranks of Fortune 500 companies. 

Below is a recap of the C-suite developments at America’s highest-revenue-generating companies announced between Sept. 5-11, 2026, organized by sector. Titles included in this roundup: CTOs (Chief Technology Officers) and CMOs (Chief Marketing Officers). We also include CEOs (Chief Executive Officers), CFOs (Chief Financial Officers), COOs (Chief Operating Officers), CIOs (Chief Information Officers), CHROs (Chief Human Resources Officers), Chief People Officers, and Chief Customer Officers when there are Power Moves within the Fortune 500 announced pertaining to those roles. 

For daily updates, subscribe to Fortune’s weekday newsletters, including CEO Daily, CFO Daily, and MPW Daily, as well as Next to Lead (weekly Mondays), and CIO Intelligence (weekly Wednesdays).

Financials

• Equinix (No. 436) appointed DD Dasgupta CMO. He previously served as VP, Product and Solution Marketing at the company and held similar roles at Cisco Systems (No. 83) and Juniper Networks, now a part of Hewlett Packard Enterprise (No. 133), before then. He succeeds Adam Berlew.

Media

• Sirius XM Holdings (No. 463) appointed Sean Gibbons SVP, Chief Product and Technology Officer. Gibbons has been with the company since 2000. Joseph Inzerillo served as the company’s EVP, Chief Product and Technology Officer until Dec. 2024 when he left to pursue other opportunities; he now serves as President of Enterprise and AI Technology at Salesforce (No. 114).

Technology

• Workday (No. 430) appointed Sarah Kennedy Ellis CMO, effective Oct. 5. She most recently served as VP, Global Marketing, Google Cloud and Google Workspace at Google, owned by Alphabet (No. 5), and held senior marketing roles at Adobe (No. 192) before that. She succeeds Emma Chalwin, who left Workday in July to become CMO of Accenture (No. 204 on the Fortune Global 500).

Source: S&P Global Market Intelligence

This story was originally featured on Fortune.com

As the new school year gets well underway, Gen Z is once again facing a daunting question: Is the degree they’re pursuing actually going to be worth it? A new ranking of America’s top 500 colleges is offering a helpful insight: they don’t necessarily need an elite name on their diploma to land a six-figure salary.

The list, compiled by Forbes, is unsurprisingly dominated at the top by Ivy League-level institutions like MIT, Princeton and Harvard, where graduates are expected to earn median salaries of more than $120,000 a decade after receiving their diploma. Graduates of the University of Pennsylvania, ranked No. 5, come out even higher, with median 10-year earnings of $151,328.

But the more surprising finding comes at the other end of the list: Most of the lowest-ranked schools put six-figure salaries well within reach.

Marietta College, a private liberal arts college in rural Ohio ranked No. 500, has median 10-year earnings of $105,837. 

In fact, nearly every school on the list has median earnings of over $90,000, meaning the earnings gap between a prestigious college and those lesser-known can be considerably narrower than students might expect.

For comparison, the median annual earnings of full-time workers ages 25 to 34 with only a high school diploma is $41,800, according to the U.S. Department of Education. The two datasets measure different populations and timeframes, but the figures still underscore the earnings premium associated with a college degree—even one from a lower-ranked school.

The college decision is about more than just salary

Post-graduation salaries are just one factor for students to consider when deciding where to go to college. Schools that repeatedly appear at the top of college rankings typically offer advantages that don’t show up in a 10-year salary figure, including expansive alumni networks, access to prominent faculty and research opportunities, and name recognition.

But any benefits come with risks and costs of their own, particularly as colleges across the country grapple with falling enrollment and mounting financial pressures.

Marietta, for example, has faced budget shortfalls that have forced it to eliminate academic programs and lay off faculty in recent years (a school’s financial health was also a factor in the Forbes ranking). In total, some 442 of the nation’s 1,700 private, nonprofit four-year colleges and universities are at risk of closing or having to merge within the next decade, according to a forecast by Huron Consulting Group.

At the same time, schools have faced growing criticism over rising tuition costs and whether degrees are delivering enough of a return on investment. The average cost of college has more than doubled over the last two decades, totaling $39,406 per student per year, including books, supplies, and daily living expenses, according to the Education Data Initiative. This has contributed to the average student now borrowing more than $35,000 to pursue a bachelor’s degree.

And for many graduates, the payoff isn’t immediate. In 2015, the unemployment rate for recent college graduates surpassed that of all workers for the first time, and since then, the gap has worsened. The unemployment rate among recent college rates currently sits at 5.7%, compared with 4.1% for all workers.

Americans’ confidence in the value of a college education has fallen alongside those concerns. In 2010, about 75% of Americans said college was “very important.” A decade and a half later, that figure has fallen to a record low of 35%, according to Gallup.

Having a degree isn’t necessarily an indicator of future success, according to CEOs like Jamie Dimon and Marc Benioff

The growing skepticism around higher education isn’t limited to students and parents. Some of America’s most prominent business leaders have also questioned whether a traditional college degree is still the best path to a successful career.

Mark Zuckerberg, who famously dropped out of Harvard University to launch Facebook (now Meta), has said college remains valuable for building relationships but questioned whether higher education is adequately preparing young people for the modern workforce.

“I’m not sure that college is preparing people for the jobs that they need to have today. I think that there’s a big issue on that, and all the student debt issues are…really big,” Zuckerberg said in an interview with podcaster Theo Von last year.

“There’s going to have to be a reckoning…and people are going to have to figure out whether that makes sense. It’s sort of been this taboo thing to say, ‘Maybe not everyone needs to go to college,’ and because there’s a lot of jobs that don’t require that…people are probably coming around to that opinion a little more now than maybe like 10 years ago,” Zuckerberg added.

JPMorgan Chase CEO Jamie Dimon, who graduated from Tufts University and Harvard Business School, has similarly argued that elite education isn’t necessarily a predictor of success on the job.

“I don’t think necessarily because you go to an Ivy League school or have great grades it means you’re going to be a great worker or great person,” Dimon said in 2024.

Skills, he added, are “far more important” than having a college degree for many jobs: “If you look at skills of people, it is amazing how skilled people are in something, but it didn’t show up in their resume.”

Salesforce CEO Marc Benioff, a University of Southern California alumnus, has gone even further, arguing that a college degree isn’t a prerequisite for creating value.

“Everybody thinks that if you don’t have a college degree, you can’t be successful in the United States, and it’s not true,” he told NBC in 2021. “You can create incredible value for the world without a college degree.”

This story was originally featured on Fortune.com

“I do everything I say—word for word. I am never a minute late. I show no excitement,” wrote Elizabeth Holmes. The line is part of an extensive handwritten note the former Theranos CEO wrote to herself when she was leading the company. 

Holmes took the stand in 2021 during the criminal fraud trial against her, and testified in court her former boyfriend and business partner Ramesh “Sunny” Balwani emotionally and sexually abused her. Part of the evidence her lawyers submitted, multiple outlets reported, included a note drawn up by Holmes detailing her schedule for the day, which began before sunrise. It appears to have been written on stationery for Raffles, a Singapore-based hotel.

Balwani’s lawyer Jeffrey Coopersmith denied Holmes’ allegations of abuse, multiple outlets reported. Coopersmith did not return Fortune’s request in 2021 for comment after Holmes’ testimony.

In 2022, a jury ultimately convicted Holmes on four counts of wire fraud and conspiracy, and she is currently serving a roughly decade-long sentence in prison. In 2025, she reportedly asked President Donald Trump for clemency to shorten her prison stay.

A new documentary is bringing renewed attention to Holmes. You Can See Everything, directed by comedian and Canadian filmmaker Nathan Fielder and American filmmaker Lance Oppenheim, premiered as a surprise screening at the Telluride Film Festival over Labor Day weekend and will be released in theaters by A24 on Oct. 16.

Filmed over about a month before Holmes reported to prison in 2023 at a beachside home in Del Mar, Calif., and continuing over three years, the nearly three-hour film follows the former Theranos CEO as she granted the crew extensive access in an apparent effort to clear her name. In it, Holmes maintains she did nothing wrong.

In some scenes, she and her partner, Billy Evans—a California hotel heir with whom she has two children—are reportedly shown making calls to prospective partners about launching a “Theranos 2.0” venture that Evans said he intended to build while Holmes served her sentence. Fielder has reportedly said Evans tried to exert significant control over the filming near the end—a dynamic some reviewers have compared to Holmes’s account of Balwani’s control over her.

Elizabeth Holmes’ mantra as a CEO

The schedule begins with a 4:00 a.m. wake up time to “rise & thank God” and ends with her lunch and dinner menus, which included broccoli, quinoa and a green drink. But what may be most notable about the schedule is what’s written below it.

“ALL ABOUT BUSINESS.”

“I am not impulsive.”

“I do not react.”

“I am always proactive.”

“I know the outcome of every encounter.”

“I do not hesitate.”

“I speak rarely. When I do—CRISP and CONCISE. I call bullshit immediately. My hands are always in my pockets or gesturing,” the last few lines of the note read. 

Elizabeth Holmes’s daily schedule

Circa 2005–2009 pic.twitter.com/hhWUBHhpbe

— Internal Tech Emails (@TechEmails) November 30, 2021

Holmes said they were Balwani’s rules and advice, The Verge reported.

“He told me that I didn’t know what I was doing in business, that my convictions were wrong, that he was astonished by my mediocrity and that if I followed my instincts I was going to fail,” Holmes testified, according to The New York Times.

A version of this story was originally published on Fortune.com on Dec. 2, 2021.

This story was originally featured on Fortune.com

Goldman Sachs just brought together around 50 Gen Zers from ultra-rich families for a deep-dive on investing, wealth management, and leadership. 

Over the course of the two-week wealth bootcamp in July, the multimillionaire 18- to 23-year-olds attended workshops led by senior Goldman Sachs leaders and industry experts in coaching and luxury. 

One morning, the Gen Zers spent nearly an hour learning how to digest Wall Street Journal articles, strengthening their confidence in reading market news and pinpointing what to take away. And in the afternoons, they’d go through a whole host of crash courses; learning the role of an equity trader from one of Goldman’s own managing directors; touring trading floors, where they got a firsthand look at deals and trades; and studying hedge fund basics and ways to create diverse portfolios. 

It was all part of Goldman’s third annual NextGS Investment Intensive Program in New York City. And learning how to understand markets and communicate effectively will come in handy as they step into generational fortunes; much of the Gen Z cohort are kids of the members of Goldman’s private wealth management division, which boasts an average account size of over $90 million, and services clients with fortunes ranging from $10 million to more than $1 billion in assets. 

“A fundamental reason we created this program was to allow the young adult children of our families the opportunity to become more confident,” Brittany Boals Moeller, region head of Goldman Sachs’ San Francisco PWM division, tells Fortune. “Many of the participants are not finance majors. They have vastly different academic backgrounds and career ambitions.”

The wealthy Gen Z cohort learned confidence, leadership, and communication skills

The programming goes far beyond the ins-and-outs of finance. With 20-something professionals often getting flak for their workplace unpreparedness, this program has made sure they’re ready to step into high-powered roles. 

The multimillionaire attendees spent an entire day sharpening their communication, presence, and leadership skills with coaching company LifeHikes CEO Bill Hoogterp. 

Over the course of one eight-hour session, the Gen Zers were split up into pairs and told to act out scenarios in work and school, strengthening their confidence in situations like job interviews and group projects. 

Rob Kaplan, the vice chairman of Goldman Sachs, even led a session on how to reach their leadership potential, which Fortune attended exclusively—discussing ownership, ambition and personal growth. 

“They’re thinking about their first jobs. They’re thinking about how their careers are going to start, and so I actually think these concepts of leadership and communication and presence are super important for them,” Boals Moeller says. “They’re not always what you learn in school.”

The investments catching Gen Z’s eye: sports teams, crypto, and AI

The NextGS Investment Intensive Program went into all corners of the wealth basics, teaching attendees about economic cycles, fixed income, credit scores, and budgeting. But beyond traditional investing, the Gen Zers also had the chance to engage with the wealth flooding their TikTok timelines—sprawling mansions, luxury accessories, and sports ownership. 

At the tail end of the first week, the Gen Zers were introduced to arts and collectibles. They learned about major players in the art and collectibles markets, and received guidance on best practices for buying what catches their eye. The program even brought on legendary auction house Christie’s for a session on luxury watches, jewelry, and handbags. 

In week two, the cohort learned about real estate and infrastructure, exploring the market’s evolution and how to diversify their property assets.

Investing in sports was another popular session. Pouring money into soccer and football leagues has become a popular investing strategy for the ultra-rich; Jeff Bezos recently became a minority stakeholder in Liverpool F.C., and others, like Ryan Reynolds, Mark Cuban, Steve Ballmer, and Bernard Arnault have all invested in sports teams. During the session, Goldman’s young attendees explored the industry’s economics as well as ownership dynamics.

“It’s meant to allow them a glimpse into a particular industry, and I’m sure that some of our client families will be going back wanting to have a career that interlinks between investing in sports,” Boals Moeller explains. “I can definitely see that coming through.”

Aside from premier teams and Hermès pursues, Boals Moeller explains that the college-aged attendees are especially interested in private markets and alternative investments. Raised in the internet era, they grew up trading and coming across digital assets. 

Now, they’re looking to build a strong stock portfolio, invest in cryptocurrency, and ride the wealth wave of AI. Boals Moeller said that AI came up in almost every single session—not only in seeking how to decode the tech sector and the geopolitics that play into it, but also how to navigate it as a human being.

This story was originally featured on Fortune.com

For only the third time in American history, women hold more payroll jobs than men—and that trend isn’t likely to reverse anytime soon. Yet even as women pull ahead on job counts, men continue to out-earn them at nearly every stage of their careers, starting the day they leave campus.

A new study by the National Association of Colleges and Employers (NACE) found that women who graduated with a bachelor’s degree in the class of 2023 earned an average starting salary of $59,778, while men with the same degree earned $72,190. That works out to women taking home roughly 83 cents for every dollar their male classmates made—before their careers have even begun.

Women last held a payroll majority only twice before—briefly during the Great Recession around 2010, and again just before the pandemic in early 2020. Both times a downturn had wiped out male-dominated jobs in construction and manufacturing. What makes this crossover different is that it arrived without a recession.

Women have long been paid less, but they now dominate the raw number of jobs held, particularly in the post-pandemic era, when men’s employment failed to bounce back the way women’s did. Over the past 12 months, according to the Bureau of Labor Statistics, the number of employed women grew by more than 870,000, while men shed nearly 1.5 million jobs.

In a tight labor market, female-dominated fields such as health care, education, and hospitality have logged consistent gains. Men accounted for just 2% of the jobs added in August’s report, with women making up 158,000 of the 162,000 total positions created.

The imbalance has intensified concern about men’s declining presence in the workplace. Roughly 7 million fewer men are employed today than in the 1990s, and the labor force participation rate for men aged 20 and older slipped to 69.4% as of August 2026, down from 75.8% in August 2006.

Explanations vary. Some argue that video games amount to “the crisis of the American male” and are driving the retreat. Other economists, including the University of Connecticut’s Remy Levin and Daniela Vidart, contend that young men who come of age in a market defined by high unemployment and weak wages grow pessimistic about their prospects and opt out of work altogether.

Whatever the cause, the decline appears to be structural—a lasting reshaping of who fills American workplaces rather than a temporary swing tied to recession. “This seems to be more of a long-term decline that’s led to a more permanent shift going forward, or at least a semi-permanent,” Laura Ullrich, director of economic research at the Indeed Hiring Lab and a former senior regional economist at the Federal Reserve Bank of Richmond, told Fortune.

Women may be commanding workplaces, but they still aren’t commanding paychecks. They earn just 81 cents for every dollar men make, and the gap widens with age. Over a typical 40-year career, women will earn $542,800 less than men—with women of color bearing the heaviest burden, losing more than $1 million over the same span.

Why the gender pay gap persists

The very fields where women dominate—education, nursing, and care work—are the ones propping up monthly job reports, and they tend to pay less. Women make up two-thirds of workers in low-wage jobs, a concentration that widens the overall wage gap. They outnumber men in teaching by 3 to 1 and in nursing by 8 to 1, while remaining underrepresented in more lucrative fields such as finance, construction, and STEM, where they account for less than a third of the science and engineering workforce.

Parenthood, though, is the single biggest driver of the gap, especially as women get older. In the research that earned her the Nobel Prize, economist Claudia Goldin found that early-career pay gaps are relatively small—until a woman has her first child. From that point, her earnings fall and never climb at the same rate as those of men who become fathers, even when the two share identical professions and levels of education.

Men, as a rule, still shoulder less of the child-rearing. Women more often step away from work to care for children, stalling or halting their career progression, and post-pandemic return-to-office mandates have disproportionately hit the mothers who serve as primary caretakers.

So the milestone comes with an asterisk. “You could look at it and say, ‘Yay, women.’ But I don’t think it’s necessarily a positive story for women overall,” Ullrich said of August’s hiring spree.

This story was originally featured on Fortune.com

Scott Bessent has had to get used to disapproval from his former Wall Street peers during his time in D.C.—but the Treasury Secretary offered some pointed feedback in an interview at the Republican Party midterm convention last night.

Bessent, formerly a partner at Soros Fund Management and the CEO of his own macro hedge fund, Key Square Capital Management, has been criticized for Capitol Hill’s economic policies, including tariffs and, more recently, an intervention to prop up the yen and a series of extra Treasury buybacks intended to bring down the yield on U.S. bonds.

Objections to Bessent’s most recent moves have even come from famed investor Stan Druckenmiller, a friend and mentor of the Treasury Secretary.

But Bessent was sharp in his rebuttal to naysayers. Asked about tariffs and the impact of the policies on America’s working class by former White House strategist Steve Bannon last night, Bessent responded broadly: “If some of the Bloomberg Terminal bros are unhappy with what I’m doing, well, that’s too bad.”

“We have the best-performing bond market in the world, and if you look, bond yields have never been more correlated to the energy price, and that’s my point here. We have a supply shock, and we will get to the other side of this. We’ve had two very strong Treasury auctions, and the U.S.A. is in very good shape; the Treasury market is in very good shape.”

Criticism of Bessent’s recent Treasury buyback scheme stems from the fact that the department is attempting to artificially keep yields low after 10- and 30-year bond yields hit a two-decade high. (Increasing yields indicate that investors are demanding more money for the risk of holding them.) The Treasury benefits if yields are lower, as borrowing costs theoretically come down at a time when the government is running a $2 trillion budget deficit.

In buying back bonds, the Treasury reduced supply and temporarily pulled down yields. But the effect was short-lived. Inflation expectations pushed higher due to supply shocks like the situation in Iran and tariffs, and the yields on the 10- and 30-year bonds are now higher than before Bessent intervened. At the time of writing, 30-year treasuries have hit a 52-week high at 5.35%, while 10-year treasuries are also up to 4.94%.

As Druckenmiller said in his Wall Street Journal op-ed: “The U.S. shouldn’t put itself on the wrong side of that trade, not with the most important price in the world, and not when that price is trying to say the one thing Washington most needs to hear: Let the bond market speak.”

While Druckenmiller said governments defying market fundamentals “always lose,” Bessent doubled down, saying of his Japanese yen intervention: “I am the house.”

Where’s the beef?

Bessent suggested that term premiums for holding longer-dated bonds aren’t significantly elevated compared to shorter-term assets, adding: “That is telling you that investors are not demanding a premium for longer-term U.S. debt, so I’m not sure where the beef is.”

The Treasury Secretary also suggested that the fact his team received a reduced number of offers to buy back longer-dated bonds suggested investors wanted to hold onto them: “It’s a bunch of noise, and in my career I’ve made money ignoring the noise.”

Bond investors seem to be sticking to their own signals. At the time of writing, 30-year treasuries have hit a 52-week high at 5.35%, while 10-year treasuries are also up to 4.94%.

Despite concern this week about the country’s deficits, UBS’s Paul Donovan suggests bond markets are rather more focused on the inflation issue. He wrote in a note to clients this morning: “Bond markets are clearly concerned by the rapid rise in crude oil prices (U.S. gasoline and diesel prices are also shooting higher). The hope that the political cost of higher fuel prices would encourage the U.S. administration to seek reconciliation with Iran seems to have faded from markets. U.S. Treasury Secretary “House” Bessent’s bond buyback plan has had no discernible impact.”

This story was originally featured on Fortune.com

At 23, I’ve become a multi-millionaire and built two $20 million dollar companies by refusing to believe in work-life balance. This is the only truth I live by: your 20s are the cheapest years you’ll ever have to buy your 40s.

Career advisors, HR departments, and most of the internet will tell a twenty-something to protect their work-life balance at all costs. It’s framed as the mature, responsible choice, when it’s really the mechanism that keeps a person standing in the same place at 40 that they occupied at 25, because every hour spent protecting a comfortable life is an hour that didn’t go toward building a different one.

I started college at 17 and built a seven-figure social media marketing agency out of my dorm room by 18 that worked with presidential candidates and celebrities. That very company, Step Up Social, would eventually merge with online marketing agency The Candid Network. By 19, I was operating on a philosophy most people around me considered insane: say no to almost everything now, so you get to say yes to anything later. 

There’s a reason this only works when you’re this young. Your twenties are the one decade where you’re at your physical and cognitive peak at the exact moment you have the fewest people depending on you: no spouse’s career to weigh against your own, no children’s school district, no aging parents who need you nearby yet. That window closes on its own, whether you use it or not. 

I’m 23 now, and this is the truth I live by. Every sacrifice I make now is buying me the right to stop negotiating my life back one weekend at a time later on in life.

What saying “no” actually buys you

I once turned down an internship that would have paid roughly $5,000 a month, because the same hours poured into my own company were worth an order of magnitude more on a longer curve. I went out twice in college. A $100 night out was real money against what I had then, but now I don’t even register a $500 restaurant bill that’s less than 0.002% of my net worth. 

To the concern of my girlfriend, I rejected sleep almost entirely. But by averaging 3.5 hours a night, I was able to spend more time growing my businesses. It messed up my health in the short-term, but I would gladly do it all over again today. 

Most people treat “no” as a feeling, but I prefer to run the actual numbers. Skipping three years of family holidays cost me almost nothing against being able to fully cover a parent’s medical care later without blinking — a trade that bought both more time with the people I love and a far higher quality of it.

Quality is important to me. I want the top 1% of experiences, on my own and with the people who matter to me: a stake in a Formula 1 team, not a ticket to watch one; the best hotel in the world, not a Marriott or a youth hostel. 

A mentor once told me to aim for a $100 million outcome instead of a $1 million one, since hitting 10% of the bigger number beats fully hitting the small one. The same logic applies on the way in: the road to the top 1% runs through saying no to the mediocre version first.

Everyone wants the destination. Nobody wants the path.

Gen Z is being handed two instructions at once: reject traditional employment and build something of your own, but also protect your peace and “quiet-quit” whatever drains you. 

Those are opposite paths: one trades comfort for ownership, the other doesn’t leave room for ownership at all.

94% of Gen Z are so afraid of burnout that they forgo leadershipcompletely as a top career goal,  yet 76% of us still say we want to be executives eventually and 43% of Gen Z plan to start a business this year. Read that twice: the majority of my generation wants the title and the power, just not the grind it’s always taken to earn either one. You can’t want the destination that badly and refuse every path that leads there.

Plus, there’s no alpha in conformity. If you’re doing what everyone else in your graduating class is doing, it’s hard to end up with an outlier result. Schools and mainstream media preach balance because it’s the safe, defensible advice to give a room of 20-year-olds, but it’s also why economic inequality keeps concentrating. 

Balance protects the floor you’re already standing on, but it can never build you a new one.

Comfort is the real risk

With AI already reshaping which roles even exist, the twenty-somethings still optimizing for a comfortable middle are optimizing for a floor that may not hold much longer anyway.

Building a business no algorithm can fire you from is the only real job security left, and my generation can’t afford to ignore what that costs. You don’t get equity, leverage, or a business that outlives a layoff notice by staying comfortable, but by sacrificing what’s comfortable to protect what matters.

That means treating your capacity like capital: spend it where it compounds, and cut whatever quietly drains it. Showing up sharp for the meetings that actually move the needle takes real capacity, which is why I’ve cut out anything that drains it: a driver for anything over 30 minutes, a private chef who builds meals for energy instead of an afternoon crash, even training myself out of getting carsick so a routine drive doesn’t cost me a working hour. It sounds excessive until I run the math on what an hour of my best thinking is worth, and then it’s the easiest choice in the world. 

However you spend your youth, you’re deciding which version of your life you’ll be negotiating with at 40: the one you built, or the one you protected.  

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

This story was originally featured on Fortune.com

Good morning. Polymarket makes a business out of uncertainty. Now it’s bringing some certainty to its own finances by hiring seasoned CFO Warren Jenson as its first finance chief.

Jenson, who has served as CFO of Amazon, Electronic Arts, Delta Air Lines, and NBC (then a General Electric business) as well as Nielsen, will lead Polymarket’s finance organization, set financial and capital strategy, strengthen planning, and build infrastructure for its next phase, the company announced Thursday.

Shayne Coplan, founder and CEO of Polymarket, said Jenson led finance at “some of the most consequential companies in the world, and his experience will be critical to everything we build from here.”

Jenson’s hire also lands at a pivotal financial moment: Polymarket is raising about $1 billion led by the venture firm where Donald Trump Jr. is a partner, 1789 Capital, at a valuation of roughly $21 billion, which is a 40% jump from the $15 billion mark it garnered just months ago.

Jenson’s most recent CFO role was at Nielsen, where he also served as president and led the company’s modernization and analytics business. Before that, he was president at LiveRamp, where he led finance and international efforts.

“I’m joining Shayne and the leadership team to put the capital strategy and operating discipline in place to move quickly at scale and continue to push the frontier of this industry,” Jenson said in a statement.

Polymarket is a six-year-old crypto-native prediction market. The company announced in March that it was acquiring Brahma, a startup specializing in crypto and DeFi infrastructure for businesses and individuals managing digital assets, Fortune previously reported.

Instead of hiring someone from crypto or fintech, Polymarket tapped Jenson, with extensive experience at established large companies. But Shawn Cole, president and co-founder of Cowen Partners Executive Search, said he sees some synergy in Jenson’s background.

Nielsen and Polymarket share some similarities, Cole told me. “Both are data-driven businesses built around measuring, interpreting, and monetizing information at scale, with significant technology, regulatory, and institutional-market complexity,” he said.

Polymarket is working to scale its CFTC-regulated U.S. exchange and expand its global platform. It’s also hiring compliance roles that reference SEC regulatory experience, potentially signaling future filings, Cole said. “A CFO like Jenson adds credibility, public-market experience, and potentially valuable market relationships,” he said.

But Cole points out that Polymarket differs sharply from Nielsen in terms of risk. It’s operating in relatively new and evolving regulatory territory, with the potential for extensive scrutiny that could become political and involve agencies such as the Justice Department.

“That makes this a much heavier lift than stepping into an establishment like his past employers,” Cole said.

Polymarket, Kalshi, and other prediction markets allow participants to wager on probable outcomes, with contracts typically priced between 1 and 99 cents. The sector has certainly grown in popularity. Four-time NBA champion LeBron James has partnered with Polymarket on a campaign focused primarily on football.

Election-season trading, including this fall, is surging. But losses can be costly. A recent BadCredit.org study found that 79% of prediction-market users lost money in the past year, while 51% used credit cards, personal loans, or other borrowed funds to place bets.

That math is the real bet here: investors are pricing in Jenson’s ability to manage the regulatory risk, not just the accounting.

Sheryl Estrada
Sheryl.Estrada@fortune.com

This story was originally featured on Fortune.com

For Vaughn Crowe, the world of manufacturing and industrials isn’t theoretical. It’s innate. Now a VC, he grew up in Newark, historically an American industrial powerhouse.

“I was in the same neighborhood as the airport and the port,” said Crowe. “Before I knew what being a financier was, there was the thought that being a longshoreman wasn’t a bad idea. It’s a good living and I had friends who went down that path. When you’re from that environment, you can apply some critical thinking and understanding that there’s value to be created.”

Crowe, who cofounded VC firm NVP Capital with Dan Borok, has been investing in manufacturing and industrials since the firm’s beginnings in 2020. In the years since, “reindustrialization” has become something between buzzword and reality, with private capital and venture dollars flowing into the industrial base, from manufacturing to defense to energy. For a long time, those sectors weren’t seen as venture-ready. I asked Crowe: What changed?

“COVID put a spotlight on supply chain, travel, logistics, energy, power,” he said. “Healthcare is mission-critical for our country, but guess what else is? Manufacturing, shipping, and receiving. So, we were seeing where the U.S. economy was affected at scale, and that flashlight shined brightly on nursing and healthcare, of course, but also on the supply chain. Then, with geopolitical challenges around aerospace and defense, the government shifted to support mission-critical industries to help them be more self-reliant. It was a moment in time where we were recognizing these things as critical.”

AI has, of course, accelerated all of this, too. As Crowe told Fortune: “We’re at the intersection of where AI meets the physical world, and it’s impacting everything, including space, robotics, and manufacturing. We’re at the precipice of something truly revolutionary in the physical world.”

NVP has backed a wide range of companies, including Vulcan Elements, Reaxiomatic, Laborup, Outlast Power, Human Archive, Haptica Robotics, Class8, Optimal Dynamics, and Upwell. Exits, he said, will likely involve some combination of IPOs and M&A. 

“We’ll see how this plays out,” said Crowe. “For some of these legacy manufacturers, there could be a roll-up play… The options become real as you demonstrate how critical these industries are and how well they can perform. The public realm and commercial markets will also open up, and there will be enhanced chances for IPOs. There are multiple ways to create venture-like returns in this space.”

NVP closed its second fund of $80 million in 2025, and the firm is now competing in a space that’s gotten hot. (The firm was an early backer of rare earths startup Vulcan Elements, now valued at about $2 billion.) But Crowe’s gotten there early, in part because he’s been connected to it all along.

“Our firm today is in New York and San Francisco, but my experience of seeing all this live, this unique moment in time, and layering on some of my experiences growing up in an old industrial city, we know enough to be dangerous,” he said. “We can speak the language.”

A note… It’s the 25th anniversary of 9/11 today, and I’ve been thinking a lot about New York, reading stories like this with interest. I moved back in December of last year, and I’m always in our offices in Lower Manhattan. It is thriving, and I’m grateful to be here on this solemn day of commemoration—and every day. 

See you Monday,

Allie Garfinkle
X: @agarfinks
Email: alexandra.garfinkle@fortune.com

Submit a deal for the Term Sheet newsletter here.

Joey Abrams curated the deals section of today’s newsletter. Subscribe here.

This story was originally featured on Fortune.com

For Vaughn Crowe, the world of manufacturing and industrials isn’t theoretical. It’s innate. Now a VC, he grew up in Newark, historically an American industrial powerhouse.

“I was in the same neighborhood as the airport and the port,” said Crowe. “Before I knew what being a financier was, there was the thought that being a longshoreman wasn’t a bad idea. It’s a good living and I had friends who went down that path. When you’re from that environment, you can apply some critical thinking and understanding that there’s value to be created.”

Crowe, who cofounded VC firm NVP Capital with Dan Borok, has been investing in manufacturing and industrials since the firm’s beginnings in 2020. In the years since, “reindustrialization” has become something between buzzword and reality, with private capital and venture dollars flowing into the industrial base, from manufacturing to defense to energy. For a long time, those sectors weren’t seen as venture-ready. I asked Crowe: What changed?

“COVID put a spotlight on supply chain, travel, logistics, energy, power,” he said. “Healthcare is mission-critical for our country, but guess what else is? Manufacturing, shipping, and receiving. So, we were seeing where the U.S. economy was affected at scale, and that flashlight shined brightly on nursing and healthcare, of course, but also on the supply chain. Then, with geopolitical challenges around aerospace and defense, the government shifted to support mission-critical industries to help them be more self-reliant. It was a moment in time where we were recognizing these things as critical.”

AI has, of course, accelerated all of this, too. As Crowe told Fortune: “We’re at the intersection of where AI meets the physical world, and it’s impacting everything, including space, robotics, and manufacturing. We’re at the precipice of something truly revolutionary in the physical world.”

NVP has backed a wide range of companies, including Vulcan Elements, Reaxiomatic, Laborup, Outlast Power, Human Archive, Haptica Robotics, Class8, Optimal Dynamics, and Upwell. Exits, he said, will likely involve some combination of IPOs and M&A. 

“We’ll see how this plays out,” said Crowe. “For some of these legacy manufacturers, there could be a roll-up play… The options become real as you demonstrate how critical these industries are and how well they can perform. The public realm and commercial markets will also open up, and there will be enhanced chances for IPOs. There are multiple ways to create venture-like returns in this space.”

NVP closed its second fund of $80 million in 2025, and the firm is now competing in a space that’s gotten hot. (The firm was an early backer of rare earths startup Vulcan Elements, now valued at about $2 billion.) But Crowe’s gotten there early, in part because he’s been connected to it all along.

“Our firm today is in New York and San Francisco, but my experience of seeing all this live, this unique moment in time, and layering on some of my experiences growing up in an old industrial city, we know enough to be dangerous,” he said. “We can speak the language.”

A note… It’s the 25th anniversary of 9/11 today, and I’ve been thinking a lot about New York, reading stories like this with interest. I moved back in December of last year, and I’m always in our offices in Lower Manhattan. It is thriving, and I’m grateful to be here on this solemn day of commemoration—and every day. 

See you Monday,

Allie Garfinkle
X: @agarfinks
Email: alexandra.garfinkle@fortune.com

Submit a deal for the Term Sheet newsletter here.

Joey Abrams curated the deals section of today’s newsletter. Subscribe here.

This story was originally featured on Fortune.com

Good morning. On Fortune’s radar today:

• Everyone agrees that AI could kill us all. But will Congress do anything about it?
• The leaders made by September 11—and the ones it took.
• Scott Bessent picked a fight with the bond vigilantes—it’s unlikely he will win.
• Low-paid workers are getting better pay raises.
• The AI boom has already far eclipsed the dot-com boom.
• The price of Princess Diana’s off-the-shoulder “revenge” dress.
• RIP, Pumpkin Spice Latte. It’s not your season anymore.

➡️ Did someone forward this email to you? If you would like to receive this information directly, every morning before the markets open in New York, sign up here.

This story was originally featured on Fortune.com

Good morning. On Fortune’s radar today:

• Everyone agrees that AI could kill us all. But will Congress do anything about it?
• The leaders made by September 11—and the ones it took.
• Scott Bessent picked a fight with the bond vigilantes—it’s unlikely he will win.
• Low-paid workers are getting better pay raises.
• The AI boom has already far eclipsed the dot-com boom.
• The price of Princess Diana’s off-the-shoulder “revenge” dress.
• RIP, Pumpkin Spice Latte. It’s not your season anymore.

➡️ Did someone forward this email to you? If you would like to receive this information directly, every morning before the markets open in New York, sign up here.

This story was originally featured on Fortune.com

London’s stock market has endured a difficult few years, marked by a wave of delistings and IPO snubs. The number of companies listed on the London Stock Exchange (LSE) has fallen from 2,429 in 2015 to 1,534 in May 2026—a decade low —according to LSE data compiled by Statista. More than 30 have left, or are planning to leave this year, including the asset manager Schroders and easyJet, which have both agreed to U.S. takeovers.  

U.K. markets suffer from a smaller domestic investor base and shallower pools of capital than the U.S. Meanwhile years of relative underperformance have depressed valuations of London-listed companies, making them increasingly attractive for foreign buyers and private equity takeovers.  

Some business leaders are pointing the finger at the exchange itself. Octopus Energy founder Greg Jackson has said the exchange needs more “hustle” to win IPOs back. 

It’s a narrative Julia Hoggett, chief executive of the London Stock Exchange, is determined to push back on. Talk of the exchange’s decline, in her view, is overstated. 

Since joining LSE in 2021, Hoggett has driven a sweeping reform agenda designed to reverse the decline in flotations and boost capital market growth. In 2024, the U.K. rewrote its listing rules so that companies no longer need a shareholder vote for most acquisitions and gave founders more control after listing. The exchange has also reduced regulatory burdens on AIM, its junior market, to make it more attractive to international listings and has created Pisces, a new secondary market for trading existing shares.  

Hoggett says the reforms are already changing behavior. “There’s been a rise in acquisitions since the shareholder-vote rules were scrapped, and smaller companies are already using AIM’s revised rules,” she says. Total U.K. M&A value more than doubled to £124.2 billion ($167.8 billion) in the first half of 2026, according to PwC’s U.K. M&A Mid-Year Outlook, though the number of deals fell. 

The clearest sign of recovery, in Hoggett’s view, is the growing list of companies planning to list in London pipeline. “We have the largest pipeline for IPOs since 2005,” she says. “We do not have a shortage of great companies or capital. We need to stop throwing shade at ourselves as a nation, then be surprised if it’s a bit chilly and damp. We have a habit of talking ourselves down, rather than recognizing that we create world-leading companies here.” 

Britain produces more billion-dollar startups than any country besides America and China, according to the Hurun Research Institute, and topped the inaugural measuresHE Country 100 ranking in 2026, which rates national research ecosystems.  

U.K. IPO proceeds more than tripled in the first half of 2026 versus the same period last year, according to EY data. London remains Europe’s dominant capital market, recording more than twice the number of equity offerings of the next most active European exchange in the first half of 2026.  

“It [London] has long served as a gateway well beyond the continent,” Hoggett adds. London gives companies from India, China, and the Middle East a route into international capital that few other exchanges can match.  

The Uzbekistan’s National Investment Fund’s decision to begin trading on the London Stock Exchange earlier this year is one example of this. The IPO raised around $603 million and marked the first international equity offering from Uzbekistan. 

However, the Uzbekistan’s National Investment Fund listing was one of only seven London IPOs in the first half of this year. Hoggett attributes this to a broader decline in the number of companies going public. Between 1980 and 2000, an average of more than 300 companies a year went public in the U.S; in 2025, there were 90 IPOs. “The U.K. was the last major market to make that shift. I suspect that’s why commentators have mistaken a global structural shift for a specifically British problem.” 

Still, the numbers invite an unflattering comparison. The U.S. completed 72 IPOs in the first half of this year, raising $128 billion, London’s seven listings were worth $780 million. “We need to stop creating these false binaries,” Hoggett says, “especially since many U.K. companies that moved their listings to the U.S. have underperformed or failed outright.” 

Of the 21 U.K. companies that have floated in the U.S. since 2014, four are trading up, 13 have delisted, and the remaining 4 are trading down by 71% on average, according to LSE data shared with Fortune.  

“In London, even a mid-sized company can land in a major index almost as soon as it lists,” Hoggett says, triggering automatic demand from pension funds and ETFs required to hold the stock regardless of performance. In New York, that cushion is reserved for the largest companies, she adds.  

Reducing markets to “basis points, bid-cover ratios, and league tables,” in Hoggett’s view, misses the point. “Capital markets are a vital, direct driver of growth, jobs, and national prosperity that most countries treat as a matter of economic sovereignty.” 

Successive U.K. governments have explored ways to encourage greater public investment in the stock market. This is a move that Hoggett backs. “We need to incentivize U.K. investors to invest in the country,” she says.  

Stamp duty still applies to buying British shares, and pension and ISA tax reliefs—worth roughly £50 billion and £9 billion a year—carry no requirement that any of the capital be invested domestically. “If we are going to give you fiscal incentives to invest, we’d like at least a portion of that to be backing Britain.” 

The U.K. and Europe have historically over-indexed on holding wealth in cash accounts and housing rather than equities and higher-risk investments, Hoggett adds. “We have a culture focused on protecting people from downside risk rather than exposing them to upside potential.” 

Hoggett is betting that modernizing the exchange’s infrastructure can help London retain its competitiveness over the next decade. It is planning to let people trade digital versions of stocks through a new 24-hour platform, LSE 24, serving both institutions, who prefer the traditional 8am–4:30pm window, and retail investors, who expect to trade any time of day. 

The initiative works in tandem with a newly announced Digital Securities Depository, infrastructure built for digital shares. LSE has struck a deal with crypto exchange Kraken to explore trading digital securities alongside traditional stock. Client testing begins by the end of this year and LSE 24 is expected to go live in the first half of 2027. 

“Most founders put their money, their mortgage, and quite often their marriage on the line to create great companies,” Hoggett says. “We as a society should respect the fact that they’re taking that risk. My job is to continue to make the U.K. ecosystem as effective as possible to make it more straightforward for them to achieve those aspirations.” 

For the latest coverage and updates from Fortune CEO Forum, as well as insights into the companies on our list, visit this page.

This story was originally featured on Fortune.com

London’s stock market has endured a difficult few years, marked by a wave of delistings and IPO snubs. The number of companies listed on the London Stock Exchange (LSE) has fallen from 2,429 in 2015 to 1,534 in May 2026—a decade low —according to LSE data compiled by Statista. More than 30 have left, or are planning to leave this year, including the asset manager Schroders and easyJet, which have both agreed to U.S. takeovers.  

U.K. markets suffer from a smaller domestic investor base and shallower pools of capital than the U.S. Meanwhile years of relative underperformance have depressed valuations of London-listed companies, making them increasingly attractive for foreign buyers and private equity takeovers.  

Some business leaders are pointing the finger at the exchange itself. Octopus Energy founder Greg Jackson has said the exchange needs more “hustle” to win IPOs back. 

It’s a narrative Julia Hoggett, chief executive of the London Stock Exchange, is determined to push back on. Talk of the exchange’s decline, in her view, is overstated. 

Since joining LSE in 2021, Hoggett has driven a sweeping reform agenda designed to reverse the decline in flotations and boost capital market growth. In 2024, the U.K. rewrote its listing rules so that companies no longer need a shareholder vote for most acquisitions and gave founders more control after listing. The exchange has also reduced regulatory burdens on AIM, its junior market, to make it more attractive to international listings and has created Pisces, a new secondary market for trading existing shares.  

Hoggett says the reforms are already changing behavior. “There’s been a rise in acquisitions since the shareholder-vote rules were scrapped, and smaller companies are already using AIM’s revised rules,” she says. Total U.K. M&A value more than doubled to £124.2 billion ($167.8 billion) in the first half of 2026, according to PwC’s U.K. M&A Mid-Year Outlook, though the number of deals fell. 

The clearest sign of recovery, in Hoggett’s view, is the growing list of companies planning to list in London pipeline. “We have the largest pipeline for IPOs since 2005,” she says. “We do not have a shortage of great companies or capital. We need to stop throwing shade at ourselves as a nation, then be surprised if it’s a bit chilly and damp. We have a habit of talking ourselves down, rather than recognizing that we create world-leading companies here.” 

Britain produces more billion-dollar startups than any country besides America and China, according to the Hurun Research Institute, and topped the inaugural measuresHE Country 100 ranking in 2026, which rates national research ecosystems.  

U.K. IPO proceeds more than tripled in the first half of 2026 versus the same period last year, according to EY data. London remains Europe’s dominant capital market, recording more than twice the number of equity offerings of the next most active European exchange in the first half of 2026.  

“It [London] has long served as a gateway well beyond the continent,” Hoggett adds. London gives companies from India, China, and the Middle East a route into international capital that few other exchanges can match.  

The Uzbekistan’s National Investment Fund’s decision to begin trading on the London Stock Exchange earlier this year is one example of this. The IPO raised around $603 million and marked the first international equity offering from Uzbekistan. 

However, the Uzbekistan’s National Investment Fund listing was one of only seven London IPOs in the first half of this year. Hoggett attributes this to a broader decline in the number of companies going public. Between 1980 and 2000, an average of more than 300 companies a year went public in the U.S; in 2025, there were 90 IPOs. “The U.K. was the last major market to make that shift. I suspect that’s why commentators have mistaken a global structural shift for a specifically British problem.” 

Still, the numbers invite an unflattering comparison. The U.S. completed 72 IPOs in the first half of this year, raising $128 billion, London’s seven listings were worth $780 million. “We need to stop creating these false binaries,” Hoggett says, “especially since many U.K. companies that moved their listings to the U.S. have underperformed or failed outright.” 

Of the 21 U.K. companies that have floated in the U.S. since 2014, four are trading up, 13 have delisted, and the remaining 4 are trading down by 71% on average, according to LSE data shared with Fortune.  

“In London, even a mid-sized company can land in a major index almost as soon as it lists,” Hoggett says, triggering automatic demand from pension funds and ETFs required to hold the stock regardless of performance. In New York, that cushion is reserved for the largest companies, she adds.  

Reducing markets to “basis points, bid-cover ratios, and league tables,” in Hoggett’s view, misses the point. “Capital markets are a vital, direct driver of growth, jobs, and national prosperity that most countries treat as a matter of economic sovereignty.” 

Successive U.K. governments have explored ways to encourage greater public investment in the stock market. This is a move that Hoggett backs. “We need to incentivize U.K. investors to invest in the country,” she says.  

Stamp duty still applies to buying British shares, and pension and ISA tax reliefs—worth roughly £50 billion and £9 billion a year—carry no requirement that any of the capital be invested domestically. “If we are going to give you fiscal incentives to invest, we’d like at least a portion of that to be backing Britain.” 

The U.K. and Europe have historically over-indexed on holding wealth in cash accounts and housing rather than equities and higher-risk investments, Hoggett adds. “We have a culture focused on protecting people from downside risk rather than exposing them to upside potential.” 

Hoggett is betting that modernizing the exchange’s infrastructure can help London retain its competitiveness over the next decade. It is planning to let people trade digital versions of stocks through a new 24-hour platform, LSE 24, serving both institutions, who prefer the traditional 8am–4:30pm window, and retail investors, who expect to trade any time of day. 

The initiative works in tandem with a newly announced Digital Securities Depository, infrastructure built for digital shares. LSE has struck a deal with crypto exchange Kraken to explore trading digital securities alongside traditional stock. Client testing begins by the end of this year and LSE 24 is expected to go live in the first half of 2027. 

“Most founders put their money, their mortgage, and quite often their marriage on the line to create great companies,” Hoggett says. “We as a society should respect the fact that they’re taking that risk. My job is to continue to make the U.K. ecosystem as effective as possible to make it more straightforward for them to achieve those aspirations.” 

For the latest coverage and updates from Fortune CEO Forum, as well as insights into the companies on our list, visit this page.

This story was originally featured on Fortune.com

Your company just activated the most capable technology it has ever bought. The AI assistant arrived the way the 18 systems before it arrived — the CRM, the HRIS, the data platform, the two collaboration suites that do the same thing — with a launch email, a recorded webinar you attended in spirit, and a dashboard showing near-total activation by Friday. Ask what it has changed about the output and you get a shrug and a workaround somebody built in a spreadsheet. Activation is magnificent and output is flat, and every executive reading this has sat in that meeting. MIT put a number on it last year: 95% of corporate generative AI pilots produced no measurable return.

American schools just ran the same play, at national scale, and are about to be graded on it. The interactive whiteboards, the laptop carts, the platforms bought with pandemic money — each one activated without the training and instructional model built around it. There was always an alibi — the tool was clunky, the migration was botched. AI takes the alibi away. This time the technology is genuinely excellent, and the results still are not moving. That settles an argument the software industry has dodged for a decade: the constraint was never the tool. It is everything nobody builds around it — the training, the workflow, the taught habit of using it well. AI makes the shift from adoption to outcomes undeniable, and Washington last week started asking schools for proof.

Coming out of the pandemic, I watched a version of this play out in our schools as they tried to implement a new wave of career exploration beyond the standardized test and the familiar conversation with a guidance counselor. As policymakers began asking whether college was really the right destination for every student, states invested in technology designed to help teenagers figure out what they were good at, what they liked and where those things might lead.

Some of the best game designers in the country helped build remarkably sophisticated career-exploration tools. Then reality arrived: no 15-year-old was simply logging on to plan their future. Schools had to carve out time during the school day and pay career coaches to get students through the experience. And even then, identifying a promising career meant little unless somebody had brought employers to the table to create an internship, apprenticeship or actual job at the other end. I had a front-row seat to the policy that created the demand, and then to what companies had to do to make it work. The technology wasn’t bad. The policy wasn’t wrong. We funded the tool and underestimated everything required around it to produce the outcome.

That is the pattern Washington is now beginning to confront in AI. Until last week, the policy conversation shoved everything into one bucket labeled kids and screens. A teenager scrolling six hours of algorithmic video and a sophomore working through a chemistry sequence her school cannot staff are both, technically, children looking at glass. Treat them as one problem and you will solve neither.

The Department of Education pulled them apart last week, in guidance most people read as a screen-time document and that deserves a more consequential reading. Its central move is one your IT department made years ago: recreational technology and instructional technology are not the same thing, and screen time is a lousy measure of educational value. That is a defense of the category, and the industry should take the win.

Then comes the invoice. Having defended instructional technology, the guidance immediately raises the bar on it, AI included. Judge products by demonstrated learning outcomes rather than usage. Build evidence into renewals, not just purchases. Expect vendors to publish independent evaluations and disclose what their products cannot do. Responsible design, the Department writes, is the floor. This is not the end of edtech but the beginning of its accountability era. The message underneath is not use less technology. It is: prove it works.

That surfaces a problem the industry has consistently underpriced: implementation.

There are AI tutors available right now, some of them free, that are patient, competent, available at eleven at night — more help than most students could otherwise get. In a two-year randomized trial across 18 Tennessee middle schools, 96% of students tried the AI tutor at least once, then turned to it in only 17% of the moments when they had gotten something wrong. The tutor was one click away, and students walked past it at precisely the moment it was built for, because when you are stuck, the cheapest available move is to skip. A companion experiment points in the same direction: students performed better after mistakes when the software made them slow down and review their work, and the most encouraging learning gains came when the AI was embedded in a mastery-based workflow. The evidence is early; the lesson is not. The gap between a capable tool and a learning outcome is closed by design and adult decisions, not exposure.

That is your data platform. That is your AI assistant. Nobody was taught the work. The login was treated as the finish line, and it never is, in your building or theirs.

Schools bought technology on the same theory, with pandemic money that had to move fast. The hardware arrived; the instructional model did not, and now the money is gone, leaving implementation an unfunded expectation in a million classrooms. This is not a complaint about teachers; it is the opposite. We would never install a sophisticated new imaging system in a hospital, hand a physician a login, and call the implementation finished. Using an AI tutor or a clinical simulator well is professional practice, not intuition, and we have been buying the first half of that equation while expecting the second half free.

Implementation is not just about teaching teachers where to click. It is increasingly about teaching students how to use powerful tools without outsourcing the thinking to them. Handed a capable model and a hard problem, those students sent it bare answers and moved on — the digital equivalent of asking a colleague to just do it for you. That is the habit their employers will spend the next decade paying for, or paying to break. They are graduating into work where using AI well means knowing when to push back on it, when to make it show its reasoning, and when to close it and think. Almost nobody is teaching that on purpose. We are hoping it accrues from exposure — the theory behind your company’s activation dashboard.

Statehouses have moved faster than Washington. Alabama will require a computer science course including AI instruction to graduate, beginning with the class of 2032; Idaho has directed its education department to build a statewide AI framework; FutureEd is tracking 77 AI-in-education bills across 27 states this session; the OECD will test students on media and AI literacy through PISA in 2029. Every one of those mandates depends on an adult in the room who knows how to teach it, and we are legislating AI literacy faster than we are producing anyone qualified to deliver it.

The same implementation problem becomes a capacity problem in career education, where expertise cannot simply be downloaded. Roughly 600,000 skilled trades jobs were posted last year against about 150,000 new workers entering through apprenticeships, and nursing schools turned away nearly 93,000 qualified applications in a single year for lack of faculty and clinical placement sites. One instructor retires in a rural county and the pathway disappears with her, along with the only local route into a job that pays. The binding input there is a person and a room, and no simulation manufactures a preceptor. But technology can travel where scarce expertise cannot, and students who arrive at scarce lab time already fluent use it better than those starting cold. AI shouldn’t replace the teacher. It should extend the reach of the teacher we can’t find enough of.

None of this is an argument against the technology. A higher bar is very good news for serious firms and fatal for everyone selling a login. Training stops being a customer-success cost center and becomes part of the product. Your company already learned this lesson, expensively and mostly in private. Schools are about to learn it in public, with a labor shortage waiting and a federal guidance document telling everyone to show their work.

The tools are extraordinary. The question nobody asked when they bought them is the only one that matters now: does anyone here actually know how to use this?

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

This story was originally featured on Fortune.com

Your company just activated the most capable technology it has ever bought. The AI assistant arrived the way the 18 systems before it arrived — the CRM, the HRIS, the data platform, the two collaboration suites that do the same thing — with a launch email, a recorded webinar you attended in spirit, and a dashboard showing near-total activation by Friday. Ask what it has changed about the output and you get a shrug and a workaround somebody built in a spreadsheet. Activation is magnificent and output is flat, and every executive reading this has sat in that meeting. MIT put a number on it last year: 95% of corporate generative AI pilots produced no measurable return.

American schools just ran the same play, at national scale, and are about to be graded on it. The interactive whiteboards, the laptop carts, the platforms bought with pandemic money — each one activated without the training and instructional model built around it. There was always an alibi — the tool was clunky, the migration was botched. AI takes the alibi away. This time the technology is genuinely excellent, and the results still are not moving. That settles an argument the software industry has dodged for a decade: the constraint was never the tool. It is everything nobody builds around it — the training, the workflow, the taught habit of using it well. AI makes the shift from adoption to outcomes undeniable, and Washington last week started asking schools for proof.

Coming out of the pandemic, I watched a version of this play out in our schools as they tried to implement a new wave of career exploration beyond the standardized test and the familiar conversation with a guidance counselor. As policymakers began asking whether college was really the right destination for every student, states invested in technology designed to help teenagers figure out what they were good at, what they liked and where those things might lead.

Some of the best game designers in the country helped build remarkably sophisticated career-exploration tools. Then reality arrived: no 15-year-old was simply logging on to plan their future. Schools had to carve out time during the school day and pay career coaches to get students through the experience. And even then, identifying a promising career meant little unless somebody had brought employers to the table to create an internship, apprenticeship or actual job at the other end. I had a front-row seat to the policy that created the demand, and then to what companies had to do to make it work. The technology wasn’t bad. The policy wasn’t wrong. We funded the tool and underestimated everything required around it to produce the outcome.

That is the pattern Washington is now beginning to confront in AI. Until last week, the policy conversation shoved everything into one bucket labeled kids and screens. A teenager scrolling six hours of algorithmic video and a sophomore working through a chemistry sequence her school cannot staff are both, technically, children looking at glass. Treat them as one problem and you will solve neither.

The Department of Education pulled them apart last week, in guidance most people read as a screen-time document and that deserves a more consequential reading. Its central move is one your IT department made years ago: recreational technology and instructional technology are not the same thing, and screen time is a lousy measure of educational value. That is a defense of the category, and the industry should take the win.

Then comes the invoice. Having defended instructional technology, the guidance immediately raises the bar on it, AI included. Judge products by demonstrated learning outcomes rather than usage. Build evidence into renewals, not just purchases. Expect vendors to publish independent evaluations and disclose what their products cannot do. Responsible design, the Department writes, is the floor. This is not the end of edtech but the beginning of its accountability era. The message underneath is not use less technology. It is: prove it works.

That surfaces a problem the industry has consistently underpriced: implementation.

There are AI tutors available right now, some of them free, that are patient, competent, available at eleven at night — more help than most students could otherwise get. In a two-year randomized trial across 18 Tennessee middle schools, 96% of students tried the AI tutor at least once, then turned to it in only 17% of the moments when they had gotten something wrong. The tutor was one click away, and students walked past it at precisely the moment it was built for, because when you are stuck, the cheapest available move is to skip. A companion experiment points in the same direction: students performed better after mistakes when the software made them slow down and review their work, and the most encouraging learning gains came when the AI was embedded in a mastery-based workflow. The evidence is early; the lesson is not. The gap between a capable tool and a learning outcome is closed by design and adult decisions, not exposure.

That is your data platform. That is your AI assistant. Nobody was taught the work. The login was treated as the finish line, and it never is, in your building or theirs.

Schools bought technology on the same theory, with pandemic money that had to move fast. The hardware arrived; the instructional model did not, and now the money is gone, leaving implementation an unfunded expectation in a million classrooms. This is not a complaint about teachers; it is the opposite. We would never install a sophisticated new imaging system in a hospital, hand a physician a login, and call the implementation finished. Using an AI tutor or a clinical simulator well is professional practice, not intuition, and we have been buying the first half of that equation while expecting the second half free.

Implementation is not just about teaching teachers where to click. It is increasingly about teaching students how to use powerful tools without outsourcing the thinking to them. Handed a capable model and a hard problem, those students sent it bare answers and moved on — the digital equivalent of asking a colleague to just do it for you. That is the habit their employers will spend the next decade paying for, or paying to break. They are graduating into work where using AI well means knowing when to push back on it, when to make it show its reasoning, and when to close it and think. Almost nobody is teaching that on purpose. We are hoping it accrues from exposure — the theory behind your company’s activation dashboard.

Statehouses have moved faster than Washington. Alabama will require a computer science course including AI instruction to graduate, beginning with the class of 2032; Idaho has directed its education department to build a statewide AI framework; FutureEd is tracking 77 AI-in-education bills across 27 states this session; the OECD will test students on media and AI literacy through PISA in 2029. Every one of those mandates depends on an adult in the room who knows how to teach it, and we are legislating AI literacy faster than we are producing anyone qualified to deliver it.

The same implementation problem becomes a capacity problem in career education, where expertise cannot simply be downloaded. Roughly 600,000 skilled trades jobs were posted last year against about 150,000 new workers entering through apprenticeships, and nursing schools turned away nearly 93,000 qualified applications in a single year for lack of faculty and clinical placement sites. One instructor retires in a rural county and the pathway disappears with her, along with the only local route into a job that pays. The binding input there is a person and a room, and no simulation manufactures a preceptor. But technology can travel where scarce expertise cannot, and students who arrive at scarce lab time already fluent use it better than those starting cold. AI shouldn’t replace the teacher. It should extend the reach of the teacher we can’t find enough of.

None of this is an argument against the technology. A higher bar is very good news for serious firms and fatal for everyone selling a login. Training stops being a customer-success cost center and becomes part of the product. Your company already learned this lesson, expensively and mostly in private. Schools are about to learn it in public, with a labor shortage waiting and a federal guidance document telling everyone to show their work.

The tools are extraordinary. The question nobody asked when they bought them is the only one that matters now: does anyone here actually know how to use this?

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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• In today’s CEO Daily: A look back at how leaders confronted the crisis.
• The big leadership story: An AI warning elicits big questions.
• The markets: Mixed globally as traders await the latest U.S. consumer price index report.
• Plus: All the news and watercooler chat from Fortune.

Good morning. Today is the 25^th anniversary of the September 11 terrorist attacks. This is a different country because of those attacks, and I often think about how people from all over the world rallied to help America in its time of grief. 

I’ve also been thinking about how different leaders faced that crisis. Jeff Immelt was on a Stairmaster in Seattle, about to do a town hall on his second day as CEO of GE, when he looked up to see the second plane hit the World Trade Center. [His old boss, Jack Welch, was being interviewed about his book Straight from the Gut in a New York TV studio when the first plane hit.]

When I’d interviewed Immelt a few days earlier, he was sipping Diet Cokes and downing pretzels at GE’s Connecticut headquarters, confidently chatting about his vision for leading one of America’s largest and most valuable companies. Now, with flights grounded, he’d spend the next three days working out of a cubicle in Seattle, dealing with a clunky copier machine and spotty information as he assessed damage, dispatched help, and dealt with the fallout for colleagues, two of whom were killed. Any game-changing plans or transformative deals would have to wait. This was Management 101: call customers, communicate with employees, deploy resources, help those in need and put a well-oiled crisis plan into play.

That wasn’t an option for Commerce Secretary Howard Lutnick. As CEO of Cantor Fitzgerald at the time, he lost his brother and 657 other employees when the North Tower collapsed. Lutnick was late for work that day because he decided to drop his son, Kyle, off at kindergarten. I remember meeting with him a few weeks later and tearing up as he talked about the feeling of losing more than two-thirds of his workforce and the challenge of continuing to issue paychecks to grieving families when trading revenue collapsed. Cantor Fitzgerald continues to mark 9/11 each year by committing a full day’s revenue to charity.

Some leaders did not survive. I was sent downtown by my magazine to cover the crisis and interview survivors at local hospitals. None came.

But many did make it out alive because of people like Rick Rescorla, who was then security chief of Morgan Stanley. The Vietnam vet had long viewed the World Trade Center as a terrorist target, predicting the likelihood of a truck bomb three years before one was used in 1993. After studying how poorly that crisis was handled from a security point of view, he created an evacuation plan that he made colleagues practice repeatedly in the event of another attack. When it happened, he was ready. What’s more, he allowed his expertise and judgement to prevail over the Port Authority’s instructions for people in the South Tower to return to their desks when the first plane hit. Instead, he made everyone evacuate and is credited with initiating a wider-scale evacuation of the building that saved 2,700 lives—though sadly his was not one of them.

A total of 2,977 people died on the day of the attacks. Many more were wounded in other ways. My husband cycled furiously through Lower Manhattan that day to get home to Brooklyn. In 2020, he died of cancer of unknown primary that likely originated in his lungs. I don’t know if 9/11 was a factor, but Northwell’s World Trade Center Health Program reports that 9/11-related cancer cases jumped 75% between 2023 and 2025, with new cases on pace to grow. What I do know is that his employer, Bloomberg chairman Peter Grauer, reached out to help fund a memorial bench and Mike Bloomberg called me to offer condolences. In any crisis, the most powerful leadership trait is to share the burden of each other’s grief.

Contact CEO Daily via Diane Brady at diane.brady@fortune.com

This story was originally featured on Fortune.com

We know, we know. We spend too much time on our phones, we’re too glued to our screens, etc. And yet, screen time, the number everyone tracks—yet few people actually change their behavior due to that number—may be measuring the wrong thing.

Two separate studies have now quantified how much time you spend on your phone matters a lot less than how you spend it. It’s the latest data point in how digital life is quietly reshaping the ordinary rhythms of American daily life, from where people spend their free time to how they spend the hours on their phone instead.

A seven-month study out of Aalto University in Finland tracked 277 people across desktop and mobile devices, logging more than 13 million events measuring information overload and found that total time online barely predicted how overloaded people felt. What did was something they call “session sparseness”—short, repeated check-ins throughout the day, rather than one longer stretch of use.

“Screen time does matter, but the heaviest users aren’t the most overloaded,” said Henrik Lassila, the study’s lead author. “Those who feel most overwhelmed are the ones who return to their phone again and again for brief moments and then put it down shortly after.”

The effect was concentrated in the morning. Mobile use before noon predicted overload; evening or afternoon use largely didn’t, and desktop use didn’t either. The researchers also tested whether specific content—news, shopping, or social media—drove the effect, and it didn’t. Only messaging sessions stood out, and only because they tend to be the most fragmented, not because messaging itself is harmful.

“We feel overloaded when we can’t process all the incoming information and our minds feel ‘full’ or stressed,” Lassila said. “Information overload is linked with negative emotions, which can, in turn, drive more checking—a vicious cycle.”

Nix the brain rot

A second study says it also matters what you’re actually looking at. Researchers at Karabük University in Turkey surveyed 439 adults about “brain rot,” the term Oxford named its 2024 word of the year for the mental fog tied to compulsive short-form content. The researchers defined it as cognitive overload and fatigue driven by passive, algorithm-fed consumption of low-quality, fast-paced content.

Unlike Aalto’s finding, this study found the type of content mattered a great deal. Brain rot significantly predicted burnout on its own, and burnout then became a chain reaction: It fed into stress and anxiety, and that combination ultimately predicted depression.

The paper draws a sharp line between brain rot and behavioral addictions like gaming disorder. Gaming addiction, the researchers note, involves high arousal and active, goal-directed engagement. Brain rot looks nothing like that. It’s closer to what researchers elsewhere have called “zombie scrolling”—a lethargic state in which people are neither stimulated nor actively trying to stop, just passively surrendering to whatever the algorithm serves next. The brain rot researchers frame the fog and numbness that follow not simply as damage, but as the mind’s own defense mechanism: a deliberate, energy-conserving shutdown that kicks in once sensory input outpaces what a person can process.

The authors describe brain rot as triggering a “loss spiral,” depleting people’s cognitive and emotional resources before that depletion cascades into further distress. Burnout, they write, “emerged as a pivotal transitional factor” in that chain, and the model explained 65% of the variance in depression once the full pathway was accounted for.

Put together, Aalto’s data says the pattern of checking predicts how overloaded you feel, regardless of what you’re checking. Karabük’s data says the type of content predicts whether you burn out, regardless of how often you check it. It suggests two different things are happening to people at once and that neither pattern-of-use nor type-of-content alone explains the whole picture.

This story was originally featured on Fortune.com

Gen Z workers may know their way around the latest gadgets and AI tools better than anyone. But bosses consistently have one complaint about their young new hires: They lack basic people skills. Schools taught them how to type and code, but not how to speak up in a meeting.

One exec took matters into his own hands. Richard Roper, president of Marsh People and Investment (Hong Kong & Macau), is a father of three: a zillennial, a Gen Zer, and a Gen Alpha. When his two eldest daughters were ready to start working, he didn’t just wish them luck.

Instead, he handed them a list of “daddy tips,” distilling three decades of career advice into one cheat sheet. “I spent some time and wrote them a full sheet of ‘daddy tips’ of trying to pass on my work experience of all these years to them,” he said at the Fortune Leaders Forum in Macau on Sept. 8.

“It was a lot of the basics which are now coming around to be very valuable,” Roper explained. “Being enthusiastic, being polite, being respectful to your bosses… always bringing value to a meeting. It sounds quite old-fashioned, but all of those human skills.”

Now both his daughters have jobs, and Roper says the basics he taught them matter more than ever in the age of AI. “Being able to influence, have a story on entering a room, all this kind of stuff, now is really great currency for them.”

Research shows Gen Z is in desperate need of human skills

Roper’s advice might sound simple, but teaching the next generation to show up on time, be polite, and speak up in meetings could give them an edge in today’s job market. With Gen Z struggling to land entry-level roles—many of which can now be done by AI—employers are looking for exactly those “old-fashioned” people skills more than ever.

Soft skills are increasingly rare among Gen-Z workers. Employers repeatedly warn that their young new hires don’t know how to interact with coworkers or clients, haven’t got the skills to work with people who have different opinions, and aren’t clued up on basic office etiquette like what to wear. One in five young candidates even bring their parents to job interviews, as they struggle to share with employers what skills they bring to the job or what their salary requirements are.

Gen Z isn’t completely unaware of their shortcomings: In fact, data compiled in 2024 by Harris Poll showed that 65% of Gen Z workers admitted that they don’t know what to talk about with their coworkers. This worry is heightened among young staff who entered the workforce post-pandemic; the COVID-era cohort is more than twice as likely to struggle with plucking up the courage to start a conversation with colleagues than those who worked before the pandemic.

While some workplaces have resorted to firing their unprepared staffers, others are trying to plug the gap in the form of etiquette classes and soft skills training—including lessons on how to speak up in meetings.

Roper isn’t the only boss to take his kids’ education into his own hands. Grindr’s CEO George Arison is even planning to bring his two children to the office to shadow him once they hit 10 years old. The Soviet-born exec said that watching him pull 12-hour days won’t just teach them how to run meetings or use the printer, but will show them “grit”.

“I still work insanely hard,” he told Fortune. “I think seeing what I do and how important the love for work is will be really crucial.”

The ‘daddy list’—read the tips a Marsh exec shared with his daughters before they joined the workforce

• It is easy to stay ahead of the pack and stand out if you think about it and try a little harder than the rest
• Be positive, enthusiastic, punctual and polite- attitude over aptitude every time
• Find a career you love and you will never ‘work’ another day of your life
• Think about what your boss is looking for and make their lives easier, until you are the boss
• First impressions count at interview, on your first days and in meetings. Get an early win to spread a positive vibe about ‘the new girl”
• Network at work, be kind to people below you and at the same level, you will need them at some point
• Try different things until you find something you like
• No one is ready for a promotion, just accept the job and learn once you have it
• Freedom means a lot, the ability to not be stuck at your desk and do generally what you want is liberating
• Some things pay more than others for the same effort- investment banking and consulting firms pay huge, teaching and nursing pay less. It’s not about your value to society its value to the company. Choose what makes you happy

This story was originally featured on Fortune.com

This weekend, a rocket lifted off from a launch pad on a remote Norwegian island and did something no private European space company had ever done before: it reached orbit. Isar Aerospace’s Spectrum vehicle powered through max dynamic pressure, separated its first stage, ignited its second stage, and crossed the Kármán line before completing the burns needed to place its payloads into the right orbit. It was, in the words of Isar’s CEO Daniel Metzler, the moment Europe had its own space capabilities.

For decades, European companies have built extraordinary satellites, telescopes, and space science programs but have steered clear of getting them into orbit. Launch has long been the single biggest bottleneck in the global space economy: the chokepoint that determines who gets to put hardware in orbit, on what timeline, and under whose terms. Isar’s flight is the first proof that a European company can open that chokepoint from European soil, for commercial and Allied sovereign customers, without waiting on anyone else’s manifest.

This is crucial for the ability of the Alliance to deter adversaries and, if needed, defend themselves, as well as for the creation of resilient economies. Modern connectivity, surveillance, and information advantage all run through satellites. NATO itself has said as much: since 2019, the Alliance has formally treated space as an operational domain, on par with air, land, sea, and cyberspace. Positioning and timing, missile early warning, weather forecasting for mission planning, secure satellite communications, and intelligence, surveillance and reconnaissance all depend on getting the right satellites into the right orbits, repeatedly and on schedule. If Allies cannot launch their own satellites close to home, they cannot fully control their battlefield communications with deployed forces, or rapidly respond to potential threats.

NATO allies already own or operate more than half of the world’s active satellites, and the Alliance is building ambitious shared constellations to knit them together, but those constellations are only as good as Allies’ ability to get replacement and augmentation payloads into orbit on short notice, which is exactly the gap STARLIFT is meant to close, and it’s why Isar Aerospace’s successful second Spectrum launch matters: it hands STARLIFT’s multinational access-and-launch framework its first proven, sovereign European vehicle to actually call on.

A single point of failure in getting hardware to orbit — whether a shortage of vehicles, a single dominant provider, or a geopolitical disruption — is a vulnerability that adversaries can and will exploit. Isar’s model, which pairs a flight-proven vehicle with a vertically integrated factory capable of building up to 40 rockets a year and a second launch site under construction in Nova Scotia, is designed to remove that single point of failure and make Allied launch a repeatable, scalable capability.

Access to space is also critical for deterrence. NATO leaders have already determined that an attack to, from, or within space could trigger the Alliance’s collective defence commitments, and the Alliance is explicit that space today is “contested, congested and competitive,” adversaries’ counter-space technologies threatening to restrict Allied freedom to operate there. Deterrence increasingly depends on the ability to replace, reconstitute, and disperse space capability faster than an adversary can degrade it. Distributed, commercially built, rapidly reproducible satellite and launch infrastructure is key to that effort, enabling the real-time surveillance, resilient communications, and faster targeting cycles that deterrence ultimately rests on.

None of this happens, though, unless Allied governments do their part on the demand side. NATO’s own Commercial Space Strategy, endorsed by defence ministers in February 2025, states plainly that cutting-edge space technology “is no longer limited to state actors” and commits the Alliance to lean more heavily on commercial providers and keep their services available in peacetime, crisis and conflict alike. Isar’s own order pipeline, and its ability to manufacture rockets at scale, exists because institutional and commercial customers were willing to buy before the technology was fully proven. Allied governments, defence ministries, and space agencies need to act as anchor customers, paving the way for new capabilities to emerge and for the rest of the market to then follow.

Isar’s flight from Andøya proved that Europe can build and fly its own rockets. The next stage is for Allies to act as anchor customers to continue developing the most needed capabilities at a commercial scale.

Patrick Schneider Sikorsky is a Partner at the NATO Innovation Fund and David Ordonez is a Senior Associate at the NATO Innovation Fund

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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Asia’s tourist destinations are overrun with visitors, testing the patience of residents in hotspots like Kyoto and Bali. Some governments are trying to limit the influx of visitors through measures like taxes or reduced visa stays. 

Ethan Lin, co-founder of the Asia-based travel platform Klook, argued at the Fortune Leaders Forum in Macau on Sept. 8 that thinking of overtourism as a pure numbers problem misses the real source of the issue.

“Overtourism is a concentration problem, not a volume problem,” Lin said. In other words, too many tourists are going to the same small number of places within a country, rather than experiencing everything a destination has to offer. 

AI may help tourists find something new to do or see. In Klook’s Travel Pulse survey of Gen Z and millennial travelers across Asia, 57% said they had used AI to find new destinations or experiences. “Technology and AI help to diversify [tourism] traffic into different and lesser-known destinations,” Lin said. 

Speaking on a separate travel-focused panel, David Mann, Mastercard’s chief APAC economist noted that, per company data, those who pay for AI subscriptions are more likely to visit places off the beaten path. “People are looking to discover more places, more hidden gems, and plenty of places they’ve never tried before,” he said. AI “can really help them to find that even more effectively.”

Hospitality operators, too, have leaned on social media influencers to raise awareness about their offerings. Myoko Suginohara Ski Resort in Japan, for instance, recently collaborated with American snowboarder Travis Rice to showcase the appeal of its mountains for backcountry skiing and snowboarding. 

“For two seasons, he brought a crew to film top boarders snowboarding down the mountains in Myoko,” Ken Chan, the founder of Singapore-based Patience Capital Group, which owns the resort, said. “This makes viewers want to have that experience, and [encourages them to] come over to Myoko.”

Driven by experiences

Travel today is also heavily driven by experiences, from concerts to sporting events. Jane Sun, CEO of Trip.com, said demand was driven by the “three Ps”: premium, purposeful, and pro-leisure travel. 

The most expensive package Trip.com has ever offered, a $200,000-per-person tour, sold out in 17 seconds, Sun said.

“Young people like to go to G-Dragon, Blackpink and Jay Chou shows,” she added. “NBA games and F1 car races are also very popular—the tickets [on our platform] sold out almost instantly.” 

In Macau, integrated resorts are now staging their own experiences to diversify away from their reliance on gaming, dining and shopping. SJM Resorts hosts the Macao Open golf tournament, while Melco-owned City of Dreams stages “House of Dancing Water,” an aquatic spectacle of aerial acrobatics.

“They come for the golf, but they’ll stay for the dining, the hotel, and the holistic experience we offer here in Macau,” said Gerard Walker, SJM’s chief hospitality officer. (SJM Resorts was a host partner for the Fortune Leaders Forum.)

Finally, today’s travelers are turning their flexible working arrangements into “workcations,” performing their regular job duties from a holiday destination rather than an office. “Lots of people work Monday through Thursday. On Friday, they will fly their family [out and] spend a long weekend,” Sun said. 

“It’s just more fun. When we’re in our own home city, we tend to be more lazy on weekends, deciding to just stay in or head out for [a quick] dinner,” Lin said during his session. “But when they travel, they have to spend more.”

This story was originally featured on Fortune.com

After a long week at work, the perfect Saturday for some people involves grabbing coffee with friends and walking around, spending the hard-earned money they toiled all week to earn. Shopping can be a form of therapy—it’s something even Cher Horowitz understood in Clueless. But Silicon Valley has a different idea: Shopping is a chore best handed to artificial intelligence.

On Tuesday, Meta became the latest tech giant to join the AI shopping rush, with Muse: a personal agent that can use years of social activity to understand a consumer’s taste, search for products, navigate checkout, and prepare a purchase for final approval. It joins a rapidly expanding crowd of AI personal shoppers from Amazon, Google, Walmart, Disney, Uber, and OpenAI, all competing to control the increasingly valuable journey between wanting something and paying for it.

Muse, which will initially roll out to U.S. adults for free, can act autonomously on a user’s behalf to complete tasks, ranging from messaging friends and planning a night out to shopping for a vacation outfit.  Unlike a conventional chatbot that suggests products or compares prices, Muse can navigate checkout and pay through Stripe’s Link service after presenting the total for the consumer to approve, according to Meta.

But the industry’s eagerness to automate shopping is running ahead of consumers’ willingness to actually surrender it. Some consumers are already embracing AI for parts of the shopping process: traffic from AI-powered assistants and chatbots to retail websites jumped 693.4% during the 2025 holiday season, according to Reuters. Online holiday spending reached a record of $257.8 billion during the period, up 6.8% from the previous year. 

However, that may be the extent of how much consumers want AI in their shopping cart. Only 31% of respondents to a Vogue Business survey said they would outsource shopping to an AI agent, even if it understood their taste and purchase history. Just 24% trusted recommendations and summaries produced by AI chatbots, while 72% said they would not share card details, 46% would withhold their browsing history, and 40% would not provide location data.

More than half of the respondents had never used AI to shop for fashion or beauty, and only 2% said it consistently understood their personal style. Consumers were more receptive to using AI as an assistant than allowing it to become the buyer, with some worried that making purchases too automatic could cause them to lose control of their spending—and that’s because asking AI to find the cheapest TV is different than letting it pick and choose one for you.

Meta’s data advantage comes with privacy baggage

Shopping is personal not only because people enjoy doing it, but because what they browse, want, and ultimately buy can say a lot about who they are.

Most shoppers appear more interested in using AI to find deals or narrow their options than allowing agents to choose products and spend their money. Meta, however, has access to years of information about what people watch, follow, save, and share—giving it a window into not only what consumers might buy, but who they are.

Muse can remember information a user shared once and turn a recipe reel saved on Instagram into a grocery list, according to Meta. The memory could make Muse an unusually perceptive shopper, but it requires access to increasingly personal information. Meta says users choose which apps Muse can connect to and how much access it receives, can disconnect services at any time, and can opt out of having their interactions used to train its AI models. The company also says Muse conversations and data will not be shared with its advertising systems.

Those safeguards must overcome Meta’s long history of backlash over how it collects and uses personal information, including a record $5 billion Federal Trade Commission penalty in 2019 over allegations that Facebook violated users’ privacy. Muse is now asking consumers to grant Meta access to even more personal information in exchange for better recommendations. The more Muse knows, the more useful it could become—but trusting Meta to turn personal data into purchases is a much bigger ask.

Muse also represents a consumer-facing test of CEO Mark Zuckerberg’s costly effort to put Meta back at the front of the AI race. After its previous model, Llama 4, was widely panned, Meta spent $14.3 billion for a 49% stake in Scale AI, hired its cofounder Alexandr Wang as chief AI officer, and committed hundreds of billions of dollars to AI infrastructure. Muse runs on Muse Spark, which returned Meta to the race without consistently beating models from OpenAI, Anthropic, and Google.

Placing Muse across Meta’s social empire gives that investment a direct route into consumers’ everyday lives—and potentially the moment they open their wallets. But Meta’s ability to put another AI product in front of billions of people does not mean they want it there.

Regardless, Meta’s not the only one entering the shopping space. In May, Amazon introduced Alexa for Shopping, while Disney began testing a conversational AI personal shopping assistant inside its store app in June. Uber Eats’ Cart Assistant can turn a typed prompt or photograph of a handwritten list into a grocery cart informed by past orders. By 2030, Mastercard predicts one in 10 shoppers will use a personal AI agent to purchase products or services.

But getting there may require tech companies to recognize that shopping is not always a problem people want solved. Consumers may welcome help comparing thousands of products or finishing a tedious grocery order. Browsing without a plan, stumbling onto something unexpected, and choosing for themselves are the parts they may want to keep. The winner of the AI shopping race may be the company that understands when consumers want an agent to take over—and when they merely want someone to hold the bags.

This story was originally featured on Fortune.com

Another day, another doomsday AI post that leaves the public feeling unsettled, anxious, and unsure what to do next. At least that’s how it feels as an AI reporter who reports on this space every day. This time, the alarm bells are coming from inside the industry, courtesy of a former researcher at OpenAI and Anthropic named Jacob Coxon. His X post on Sept. 8 has gone mega-viral, racking up over 150 million views as of this writing.

“The people building AI earnestly believe that it could kill us all by the end of the decade,” Coxon said. “I spent the last three years doing pre-training research at both OpenAI and Anthropic. Neither company is acting responsibly. They are racing straight to self-improving superintelligence and gambling with our lives.”

Anthropic’s current head of alignment re-posted Coxon, noting that he is “correct” that “we really do earnestly believe AI could kill all humans!” He estimates there’s a greater than 10% chance it could happen within the next decade. And earlier this week, OpenAI’s head of research Jakob Pachocki published a blog post outlining his concerns for humanity.

Not great. So what do we do about it?

This is the first time an AI warning has truly gone mainstream

While Coxon is far from the first to warn about the perils of AI, his message might be the first to truly break into the mainstream. He promptly went on a media tour the same day he posted on X, and his message captured headlines at top news organizations. Even country singer Sheryl Crow urged her Instagram followers to take him seriously.

There are a few theories as to why Coxon’s post has spread further than previous warnings about AI. As my editor Jeremy Kahn and I discussed earlier today, anxiety about AI has reached all-time highs following recent revelations about OpenAI’s AI agents escaping their sandbox and hacking the Hugging Face website. That incident provided a tangible example of how AI can go rogue and do things that would be considered a crime if a human were involved. The public may also be more ready to hear the message right now, at a time of growing concerns about energy-sucking AI data centers and about AI’s future impact on jobs.

I also think Coxon’s authoritative confidence in the existential threat posed by AI—and the quick response by Anthropic’s head of alignment agreeing that, yes, AI could very well kill us all—underscored the gravity and the urgency of the situation.

In a first for me, Coxon’s message reached my group chat with other reporters, none of whom cover technology or AI. “Emily, any thoughts on the impending AI apocalypse and what to do about it?” my friend asked me in the group. She’s an arts and culture reporter who works in local news. It struck me as not only a good question, but the question everyone should be asking right now.

Without more information, and receipts, Coxon is more likely to create anxiety than change

The problem with Coxon’s post is that it’s vague, with no proof, and no specific examples that are easy for the public—and regulators—to act on. Yet his media tour suggests he wants his message to reach a generalized audience.

Hear me out: He claims the AI could kill us someday, but doesn’t point to any projects in the pipeline that could be shut down to avoid this. He says AI companies are moving too fast, but neglects to share screenshots, emails, or specific examples of when this behavior went sideways—when it became clear to leaders at AI companies that the technology was slipping beyond their control, for instance, and how the decision-makers disregarded the warning signs. He doesn’t suggest any new legislation, name problematic leaders that should step down, or post an in-depth look at how Anthropic researches new models and propose a new approach.

To quote another viral social media clip of Heather Gay from a 2024 episode of The Real Housewives of Salt Lake City (and at the risk of seeming glib), we need “Receipts, proof, timelines, screenshots, f*cking everything!”

That’s why tech journalist Taylor Lorenz called out Coxon for “vagueposting and fomenting fear,” noting that he offered no “actual proof and receipts showing specific instances of that negligence so that it can be corrected and so that we know what you’re talking about.” As a result, she said, the generalities in Coxon’s post will only ratchet up public fear and anxiety and lead to “terrible policy.”

Ian Krietzberg, an AI correspondent at Puck News, agreed. Coxon is “not blowing the whistle on either OpenAI or Anthropic. He’s not revealing non-public information about their practices that he finds so concerning,” Krietzberg said. “The whole thing is broad ideas-based, not specific company wrongdoing.”

So what should we do? What should I tell my arts reporter friend? Coxon doesn’t say. His main call to action is geared toward his fellow AI researchers: “If you are a lab researcher, I urge you to consider what the next few years will actually feel like. Do you want to kick off a superintelligent RL run without a rigorous understanding of its mind? Should you put your head down because “it’s happening anyway” – or take this moment to call for different conditions?”

Others have taken to social media to say people should call their legislators in response to Coxon’s post, and urge more people working in AI to speak out.

Coxon’s message still has value—just not as much as it could

There are a few things I like about Coxon’s post. The main one is that he gave up his shares in Anthropic stock upon resignation, Axios reports. That shows he’s putting his money where his mouth is. And it shields him from any criticism that he stands to make millions of dollars from Anthropic’s imminent IPO while preaching that others should not do the same.

The second thing is that he provides an opening for other researchers to say they are uncomfortable with what’s happening behind closed doors. Perhaps Coxon being light on details sets an easier precedent for others, who may not want to feel the pressure of bearing the burden of proof.

That would be a worthwhile outcome—or at least, a move in the right direction to a worthwhile outcome. I don’t share the absolutist view of the critics who accuse Coxon of doing more harm than good. This is an incredibly serious issue, and we need to hear from credible voices on the inside.

At the same time, I think we would do well to accept more specificity from these researchers, and push them to elevate the dialogue in a way that can lead to actionable change. If Coxon had been more specific, we might have already seen some.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

This story was originally featured on Fortune.com

Welcome to Eye on AI. Beatrice Nolan here. In today’s issue:

• Anthropic examines the economic impact of AI.
• U.S. accuses Chinese AI firms of industrial-scale model copying.
• Meta launches its AI agent, Muse.
• And the amount businesses spend on AI is falling.

Anthropic has three very different visions for the impact AI will have on the U.S. economy.

In the first, AI is a helpful sidekick for workers, and its impact is roughly on par with the internet. This produces real economic gains, but ones that arrive gradually, the kind of growth we’ve seen before. In the second, AI can do half of all knowledge work by 2030, mostly autonomously, though it’s not yet used for all of it. In this one, the economy grows at twice its normal rate, and while knowledge workers’ wages stall, everyone else sees gains. 

In the third, AI outperforms humans at nearly every knowledge-work task, does almost all of it autonomously, and creates essentially no new jobs to replace the ones it takes. GDP growth hits 15% a year, doubling the size of the economy every four and a half years. Society gets far richer, but unemployment climbs well past anything seen in a typical recession.

These are scenarios highlighted in new research from the company, which it released alongside an interactive tool that allows anyone to plug their own assumptions into Anthropic’s economic model and see where the economy might land. The aim, it said, is not to provide a definite answer to how AI will affect the economy but rather to illustrate various ways it could. A lot of this depends on how fast AI improves, how quickly companies adopt it, and whether it replaces workers or just helps them to do their jobs.

The model calculates GDP purely from the supply side—how much AI boosts productivity and output—without accounting for whether anyone is actually able to buy what’s being produced. If a large share of workers lose their jobs or income, that would normally reduce consumer spending, which drags down demand and causes further economic damage. The company’s own interactive tool notes that the scenario explorer “leaves out policy responses, business cycles, potential aggregate demand or financial market disruptions, and possible catastrophic risks,” calling the whole framework a “stark simplification of a complex reality.”

Anthropic said its aim is to provide economists and policy experts with some concrete scenarios about where we might be by the end of the decade.

Economists have been calling for this kind of analysis for some time. In July, more than 200 economists, executives, and researchers—including former Google CEO turned tech investor Eric Schmidt and venture capitalist Reid Hoffman, as well as economists Joseph Stiglitz, Paul Krugman, and Daron Acemoglu—signed an open letter urging policymakers to prioritize research into the likely effects AI may have on the economy and try to construct some guardrails before AI drives an economic transformation that they called “larger than the Industrial Revolution.”

Anthropic isn’t saying which future is more likely; in fact, the company acknowledges it does not know exactly how AI will affect the economy. Cofounder Jack Clark, who is Anthropic’s head of public benefit and leads the Anthropic Institute, told NPR he expects the technology itself to keep improving “at a very, very fast and sustained rate”—but thinks it will spread through the economy “more slowly” than most people assume. Much of the potential gains rely on adoption, which is often slower than many in the tech industry predict it to be. AI models may well progress to the point where they can do amazing things, but if nobody uses them, there will be minimal economic impact. 

If adoption is fast, however, many workers may find themselves out of a job. In that case, though, Clark also told NPR that the tax windfall from that growth could give policymakers room to help displaced workers—something that’s “unimaginable today.”

A companion survey from Anthropic of nearly 11,000 people found that the public expects a split outcome from AI: real productivity gains, but also some pain for workers in AI-exposed jobs. There’s a generational gap in the concerns, with people increasingly worried about younger generations and entry-level jobs getting eaten by AI. 

Not so fast

Not everyone is convinced growth will reach the dramatic level Anthropic lays out in some of its scenarios. In a new essay, economists Ben Moll and Alex Imas dismissed predictions of double-digit GDP growth in the next decade. They point out that “10 times richer in 15 years” would convert into a growth rate of 16.6% a year, which would mean the world would be 100 times richer in 30 years. 

Moll says five things would all have to go right for an AI growth explosion: automation would need to spread through the economy far faster than it previously has in history; people would need to keep spending on whatever AI makes cheap; there’d need to be enough demand to absorb all that new output; there’d need to be no major AI-related cyber incidents derailing trust and investment; and AI would need to start improving itself through automated research. Arguably, a series of rogue AI agent attacks—where models from Anthropic and OpenAI took unintended real-world actions against companies—has already damaged some trust among the public and potentially investors. That alone might slow AI adoption.   

Moll theorizes that AI insiders predict such explosive growth because they’re extrapolating from what they see in their own corner of the tech industry to the whole economy. This is the same mistake, he notes, that industry insiders made during Germany’s 2022 gas crisis.

AI adoption has not been smooth sailing, especially in larger businesses that have struggled to incorporate the technology into complex organizations. Ramp’s latest AI Index, which tracks business card and invoice spend on AI tools, found overall business adoption crept up just 0.4 percentage points in August, to 56.1%. Ramp’s own economist, Ara Kharazian, told me that outside of coding agents, he believes AI labs still haven’t built a product that meaningfully boosts productivity for most white-collar workers. 

So are we heading for economic abundance, or just a slower, stranger version of the internet age? Right now, the data seems to point to the latter. AI models keep getting more capable, but adoption, spending, and demand are all moving at a more human-scale, pedestrian pace, rather than an exponential one.

With that, here’s more AI news.

Beatrice Nolan
beatrice.nolan@fortune.com
@beafreyanolan

Correction: Tuesday’s edition of this newsletter contained a number of typos and mistakes. Mathematician Tristan Buckmaster was incorrectly referenced as “Burbank” in the final paragraph of the newsletter (he was correctly referenced earlier). In addition, mathematician Terence Tao’s first name was misspelled. The newsletter inaccurately stated that IBM’s DeepBlue was the first computer chess program to defeat a human grandmaster. It was the first to defeat a human world champion. Fortune regrets the errors.

This story was originally featured on Fortune.com

It looks like the American consumer has more to worry about than food recalls and cyclospora—a new study found that even the packaging the food comes in may pose some health concerns.

Out of over 15,000 food contact chemicals (FCCs), 1,222 or 8% can pose serious health risks, according to a recent study published in the peer-reviewed journal Environmental Science & Technology. Some of these FCCs, which in general are “substances that come into contact with food, such as through food packaging, processing, storage or other handling,” per the FDA, were found to be hazardous to human health.

Researchers from the nonprofit Food Packaging Forum Foundation, which conducted the study, found at least 2,160 chemicals regularly contact food and “migrate into foodstuffs.” Using guidelines from the UN’s Globally Harmonized System of Classification and Labeling of Chemicals (GHS), researchers found some of the chemicals related to food packaging and other materials were “carcinogenic, mutagenic, toxic to reproduction, harmful to specific organs after repeated exposure, [and] endocrine disrupting.”

That’s not the only concerning part. The researchers found that 13,211 of the 15,159 known food-contact chemicals lacked harmonized hazard data. That means the scientists could not determine from the available data whether those chemicals met the study’s criteria for being hazardous.

“There’s a lot of ways of establishing whether something is hazardous or not, and some methods are based very much just on computer models, looking at the structure, predicting something. And others are based on in vitro tests,” Dr. Helene Wiesinger, scientific communication officer at the nonprofit and one of the researchers on the study, told Fortune. “And in some sense, the data that we used?’ So this is the data we used, and the problem we ran into at that point was that there were huge data lags.”

A “regrettable substitution”

Those “data lags” have proved to be an ongoing issue throughout the food safety process. She said that it creates a problem regulators have faced across the chemicals industry—removing a known hazardous substance doesn’t necessarily solve the problem if it’s replaced with a structurally similar chemical that has also never been adequately tested.

A large majority of the chemicals that contact food regularly are under-researched and lack the necessary information to estimate their risks, Wiesinger said. She said researchers refer to this as “regrettable substitution,” where a governing body may unknowingly expose consumers to other dangerous chemicals by removing a known one.

“So take bisphenol A, and we say we don’t want to use bisphenol A anymore, so we use bisphenol S instead, because it’s functionally similar,” Wiesinger said, referring to two chemicals used in plastics and thermal receipts. “It has, in a sense, similar ways it can be used in the industry—so it’s an easy substitute. But it didn’t have enough data,” she said, to “the point where the replacement was searched for, and then bisphenol S was used, and then later, it turned out to be similarly problematic as bisphenol A.”

Bisphenol A is a common chemical found primarily in water bottles and other various products—and according to the National Institute of Environmental Health Sciences, roughly 93% of people over the age of six have detectable levels of the chemical. Bisphenol S is a common replacement for Bisephenol A—but it has been found to cause negative hormonal effects “comparable to or worse” than its predecessor, based on a study from the National Library of Medicine.

The study attempted to address that problem by looking beyond the individual chemicals. Wiesinger grouped the 15,159 FCCs according to chemical structures and identified specific “priority groups,” or clusters of chemicals structurally similar to ones already known to be hazardous. Among those groups were ortho-phthalates and known “forever chemicals” like PFASs. According to the FDA’s recall website, there have been no open recalls regarding food packaging.

About 70% of the over 4,000 chemicals fell into the priority groups, essentially meaning a hazardous chemical could potentially fly under the radar not because scientists have established that it is safe, but because scientists don’t have enough information to determine if it’s dangerous.

But Wiesinger warned that even if the conclusions of the study may be concerning for food consumers, the findings are most effective in the hands of policymakers. She said it would be “a bit of a policy failure” if a hazardous material can simply be replaced with another that hasn’t been adequately tested, and that comes with testing materials worldwide.

“Our data base is global,” Wiesinger said. “There is a lot of trade from all places to all places that we have data for.”

This story was originally featured on Fortune.com

In February 1993, weeks into Bill Clinton’s presidency, James Carville famously quipped: “I used to think if there was reincarnation, I wanted to come back as the president or the pope or a .400 baseball hitter. But now I want to come back as the bond market. You can intimidate everybody.”

What Carville was referring to is the fact that the U.S. government runs massive deficits every year, which requires the U.S. government to issue bonds to fund those deficits. In turn, other people, i.e. the bond market, have to be willing to buy those bonds we issue. That is the difference between a healthy country vs. a country like Russia, where nobody wants to buy their debt and they have to resort to cannibalization to fund spending. 

When the bond market stops buying the debt we issue, bond yields rise, increasing debt servicing costs; and quickly rising bond yields amounts to a flashing red light to stop spending and to stop issuing new debt. 

Just as Clinton had to collapse his new spending plans when faced with a bond market revolt, President Donald Trump is now learning the same lesson as bond markets are in active revolt over what the market clearly perceives to be excessive spending plans, with 30-year bond yields reaching heights unseen since before the 2008 Great Financial Crisis. 

But instead of picking up the hint, Trump only continues to throw fresh fuel on the fire, sending bond yields ever higher at the risk of sparking a self-inflicted economic crisis. 

Indeed, on Wednesday night in Dallas, at the RNC “Midterm Convention,” Trump promised that if Republicans hold Congress in November, he will “issue a dividend to every adult citizen in the United States of America for $5,000, very much like a successful company will do a cash distribution to its shareholders.”

That comparison conveniently omits the fact that companies pay dividends out of profits and generally suspend dividends when they need to pay down debt, which is the situation Washington finds itself in, running a deficit of nearly $1.8 trillion last year on top of over $40 trillion in debt. 

But far more importantly, bond markets have sold off even more dramatically in the aftermath of Trump’s $5,000 announcement, with 30-year bond yields reaching a fresh 30-year high of 5.35%, up 6 basis points today alone, and 10-year bond yields up 9 basis points to 4.92% this morning. 

Bond markets surely realize what Trump does not, which is that sending $5,000 to every adult citizen will likely end up costing the U.S. taxpayers far more than $5,000 per person, given the U.S. government will have to fund these payments by issuing new debt at currently elevated interest rates. Consider the back of the envelope math.