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McDonald’s is rolling out its cheapest value menu in years, a move that could speak more to the state of the American economy than it does fast food.

Even as sales rose for the quarter, executives at the world’s largest burger chain acknowledged in its February earnings call the fast food environment, which has pulled back in recent quarters, would “remain challenging” in 2026. Despite the company’s own progress attracting lower-income customer in the company’s fourth quarter, this tier of consumers, who have been dealing with stubborn inflation for years, are broadly pulling back on spending.

To address this issue, CEO Chris Kempczinski said during the company’s latest earnings call the restaurant chain would double down on its commitment to value and deeper discounts.

“McDonald’s is not going to get beat on value and affordability,” Kempczinski said during the call last month.

As part of the company’s latest effort to reach these consumers, McDonald’s is reportedly launching a new value menu in April with items like a 4-piece Chicken McNuggets or Sausage Biscuit priced at $3 or less. It is also revealing a $4 breakfast bundle that includes a McMuffin, hash brown, and a coffee, among other options, The Wall Street Journal reported. The new $3 menu will replace the McValue platform it launched in January 2025 that offered customers the choice of adding a second item to their full-priced order for just $1 more. 

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

McDonald’s move to value meals matches the K-shaped economy

McDonald’s newest value menu fits squarely into the trend of the K-shaped economy. While high-income people have fared well during the multi-year-stock bull run of the past few years, lower-income people have been hit by higher prices and stagnating wages. The same is happening at McDonald’s, according to Kempczinski. While high-income customer traffic is stable, the CEO warned, “lower-income consumers are particularly sensitive to value and affordability.”

McDonald’s is not the only restaurant chain looking to target these lower-income customers: Wendy’s, Burger King, and Taco Bell have all rolled out aggressive value promotions over the past year, to reach a shrinking pool of budget-conscious diners who have grown increasingly selective. 

To win over these picky consumers, Mark Wasilefsky, head of restaurant and franchise finance at TD Bank, told Fortune chains are increasingly looking for a way to provide value to consumers.

“Lower-priced options, when chosen carefully, priced at an acceptable level, and marketed aggressively, create perceived value and can generate a long-term customer,” he said.

McDonald’s value meals signal a bigger economic problem 

While Kempczinski last month touted the company’s affordability moves as part of the company getting back to its roots, some worry the new $3 menu could be indicative of broader economic problems to come.

A post by prediction market Kalshi mentioning the $3 menu racked up more than 4 million views on X, with many users jumping on the news to declare an economic downturn is near. One user who quoted the Kalshi post on X got 2.6 million views for the declaration: “Oh it’s a RECESSION recession.”

McDonald’s is betting a $3 meal will bring lower-income customers back, and yet, that may be difficult when Americans are increasingly betting that the future could hold more economic pain.

A Pew Research survey last month found 72% of people rate economic conditions as fair or poor, and nearly 40% believe conditions will be worse a year from now, compared to 31% who think they will improve. 

This pressure, Wasilefsky argues, has made value perception that much more important for chains seeking lower-income consumers, or at least those with the financial flexibility to slash prices without gutting margins.

“For those brands who can afford to do so, this is an excellent time to convince existing customers and new customers of your brand’s value and its right to have a share of your shrinking wallet,” he said.

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When Changhan Kim, CEO of the South Korean gaming company Krafton, decided he needed a way out of a costly acquisition deal, he didn’t call his lawyers—he opened ChatGPT. The result is one of the most striking cautionary tales about AI-assisted decision-making in corporate America, and it ended with a Delaware judge ordering the company reverse everything it had done.

A Delaware judge found Kim used ChatGPT to engineer the removal of Unknown Worlds Entertainment—the indie studio responsible for the underwater survival game Subnautica—CEO Ted Gill from the company to dodge a $250 million bonus payout. 

“Fearing he had agreed to a ‘pushover’ contract, Krafton’s CEO consulted an artificial intelligence chatbot to contrive a corporate ‘takeover’ strategy,” Delaware’s Court of Chancery Vice Chancellor Lori Will wrote in a ruling on Tuesday. 

In 2021, Krafton, the publisher behind the global phenomenon PUBG: Battlegrounds, acquired Unknown Worlds Entertainment for $500 million. As part of the deal, Krafton agreed to pay an additional $250 million earn-out bonus if the studio’s hotly anticipated sequel, Subnautica 2, hit certain sales targets. The contract also guaranteed that Unknown Worlds would remain independent, with cofounders Charlie Cleveland and Max McGuire, along with Gill, retaining operational control—and only being removed for cause.

Usually, it’s a good thing to hit and even exceed sales targets, but for Krafton, trouble started when their own internal sales projections showed Subnautica 2 was well on track to trigger that payout. When Maria Park, Krafton’s head of corporate development, told Kim a “dismissal with cause” would not rid the company of its $250 million bonus obligation without exposing the company to “lawsuit and reputation risk,” Kim looked toward an AI chatbot for guidance. 

Kim, spooked by what he privately called a “pushover” deal, bypassed his own legal team and turned to ChatGPT for help. When the AI chatbot responded that the earnout would be “difficult to cancel,” the ruling read, Kim didn’t accept the answer. He pushed further—and the chatbot obliged with a detailed, multi-stage corporate takeover strategy dubbed “Project X.”

Project X

ChatGPT advised Kim to form an internal task force to renegotiate the earnout or force a studio takeover; if negotiations failed, to “lock down” Steam and console publishing rights and control over the game’s code; to frame the entire conflict as being about “fan trust” and “quality” rather than money; and to prepare systematic legal defense materials while logging all communications. The chatbot even suggested drafting a public-facing message to win over Subnautica fans—a message Kim then asked ChatGPT to write. It backfired spectacularly, alarming the gaming community and heightening suspicions that something was deeply wrong at the studio.

Throughout this process, Kim’s own team warned him the strategy was dangerous, but Kim pressed ahead anyway. Cleveland, McGuire, and Gill were all removed from their roles without what the court determined was legitimate cause.

Krafton

Will found Krafton had improperly ousted the Unknown Worlds leadership, and noted company executives are expected to exercise independent human judgment—not outsource good-faith decisions to an AI. Gill has now been ordered reinstated as CEO, with the authority to bring back the cofounders. The earnout period has been extended to account for the disruption.

Neither Krafton nor Unknown Worlds responded to Fortune’s requests for comments. As of Tuesday morning, Krafton’s contact page was “temporarily offline.”

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Morgan Stanley’s Mike Wilson spent years insisting a “rolling recession” was hiding in plain sight while Wall Street celebrated what appeared to be a boom. Now he’s back with another contrarian call: half the stock market is already in a bear market, the correction has been grinding for six months, and investors panicking this week arrived late.

In a note published Monday, Wilson — Morgan Stanley’s chief U.S. equity strategist — argued that the dramatic volatility roiling markets recently is not the beginning of a selloff. It’s closer to the end. “This correction is mature in time and price,” he wrote, anchoring the call with a striking data point: 50% of all stocks in the Russell 3000 are now down at least 20% from their 52-week highs, and among S&P 500 members, the figure exceeds 40%.​

The backdrop is important. Wilson spent years arguing, often in isolation, that the economy was much weaker for many companies and consumers than what the headline economic statistics (nominal GDP or employment) suggested. Rather than a single crash, he said, weakness had moved sector by sector — tech first, then consumer goods, then the broader economy — meaning the usual markers of recession, soaring unemployment and plummeting GDP, remained muted while pain mounted underneath. He called it a “rolling recession.” Most of Wall Street thought he was wrong.​

He wasn’t. Wilson identified April 2025 — when the White House’s Liberation Day tariff announcement triggered a market capitulation — as the recession’s trough. Earnings revisions breadth staged a dramatic V-shaped rebound from that point, payroll revisions improved, and layoff data peaked and rolled over. The early-cycle recovery he had forecast was underway. And critically, it’s that recovered, reaccelerating backdrop that shapes Wilson’s read on the current turbulence.​

This week’s sell-off, he argued, has been a “correction within a bull market” — not a new downturn. It began last fall, when liquidity tightened, well before crude oil prices spiked and the VIX lurched higher in recent weeks following the escalation of the conflict in Iran. The geopolitical shock served as a “final blow” — the kind of capitulatory event that typically marks an ending rather than a beginning.​

The numbers back him up on the damage already done. Software and services stocks have been the hardest hit, with 97% of S&P 500 members in that sector trading at least 10% below their 52-week highs. Semiconductors, consumer discretionary, and financial services stocks tell a similar story. The index-level S&P 500 decline of roughly 15% from peak is real — but it dramatically understates how widely the carnage has spread beneath the surface.​

But what if the war just keeps on going?

What distinguishes today from the darker chapters of the rolling recession era, according to Wilson, is that the fundamental engine is firing. S&P 500 earnings are growing at +13% and accelerating — the opposite of the deteriorating earnings environment that accompanied prior oil-shock recessions. The crude rally is running around 40% year-over-year, well short of the 100%-plus spikes that have historically derailed business cycles. Fiscal support is substantial, with personal income tax refunds running 17% higher year-over-year, and the Fed has turned expansionary again after shrinking its balance sheet through much of last year.​

The issue, of course, is that Wilson’s analysis assumes the Iran conflict stays contained, oil stays below $100 a barrel, and the geopolitical situation resolves in “weeks, not months.” Those are enormous assumptions given the intractable nature of the Iran War, which, by all outward appearances, will go on for longer than the 3 weeks President Trump publicly estimated. History suggests geopolitical shocks have a nasty habit of defying neat timelines for resolution.

Wilson himself acknowledges the Strait of Hormuz disruption is blocking roughly 20 million barrels per day of tanker flow, and that tapping strategic petroleum reserves will only replace a fraction of that volume. If crude breaks and holds above $100 for a sustained period — which Wilson concedes would change his view entirely — the dynamic shifts from “correction in a bull market” to something more serious. The bear case isn’t some remote tail risk. It’s one escalation away.

There is one area where Wilson’s critics should be careful: his track record on calling inflection points. He was right about the rolling recession when the consensus laughed. He was right that Liberation Day marked the trough. Those calls weren’t lucky — they were built on a rigorous framework of leading indicators, breadth of earnings revisions, and liquidity tracking that most strategists missed.

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When Bernstein analyst Mark Shmulik sent a note to clients about Meta’s reported plans to cut 20% or more of its roughly 79,000-person workforce, he issued a warning. If Meta succeeds in redrawing the blueprint for an AI-enabled organization, he wrote, “others will rush to replicate it,” potentially triggering “a cascade of hurried pivots, half-formed strategies, and reactive restructuring across the ecosystem.”

The math alone is striking. Even at a 20% headcount reduction, Shmulik estimates Meta could realize $2 billion to $4 billion in cost savings this year and $5 billion to $8 billion in 2027 — translating to 3%–5% EPS upside in 2026 and 4%–7% in 2027. But he was quick to note the savings are more likely to be redeployed into AI infrastructure than returned to shareholders. Meta is already planning to spend $600 billion on data centers by 2028 and recently acquired AI startup Manus for at least $2 billion.

What makes the moment significant isn’t the scale of the cuts, but the context. Less than three weeks ago, Jack Dorsey laid off nearly half of Block’s 4,000-person workforce and made a blunt prediction to investors: within a year, most companies would reach the same conclusion. He didn’t have to wait the whole year.

Zuckerberg has been telegraphing the same logic. In January, he said he was starting to see “projects that used to require big teams now be accomplished by a single very talented person.” Reuters reported Friday that Meta is now targeting a 50:1 employee-to-manager ratio — unthinkable against the 7-to-15:1 long considered standard.

The competitive pressure is already visible elsewhere. Amazon confirmed 16,000 job cuts in January. Salesforce CEO Marc Benioff has said he “needs less heads” after cutting 4,000 from his customer support workforce. Economist Anton Korinek previously told Fortune the trend could mark “the beginning of a new era where white-collar jobs become threatened more seriously by AI. Once a few companies start the trend, competitive forces may induce others to follow suit.”

The central question Shmulik raises — and leaves open — is whether these cuts are genuinely AI-driven or whether AI is providing convenient cover for belt-tightening that would have happened anyway. “Fat exists in every organization,” he wrote, “but it’s usually not as clean as being concentrated in specific teams or individuals.”

“This is speculative reporting about theoretical approaches,” a Meta spokesperson told Fortune. That theoretical approach, of course, could set off a cascade of cuts.

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Scott Galloway doesn’t want the markets to go up. He said so out loud, live at South by Southwest, and the audience—skewing young—didn’t boo him. They cheered.

“At some point,” Galloway told the crowd during a taping of the Prof G Markets podcast on Monday, “We have to stop propping up the markets with young people’s credit cards.”

It was a throwaway line dropped near the end of a longer riff about war, oil prices, and the mechanics of economic decay. But it landed like a thesis statement—and it inadvertently explained the entire psychology behind Gen Z’s flight into prediction markets, meme stocks, crypto, and speculative gambling.

Here’s Galloway’s argument, stripped to its core: for the last 40 years, every time a genuine economic shock threatened to destroy capital—the dot-com crash, the 2008 financial crisis, the COVID collapse—the U.S. government intervened. Not to protect workers. To protect assets. To protect owners. The debt and stimulus that financed those rescues lands on younger generations.

“Rather than let assets collapse and take money from the owners and give advantage back to the earners,” Galloway said, speaking directly to Gen Z, “we’re going to pull out your credit card and ensure, in the form of debt and stimulus, that I stay rich.”

“The reason I’m economically secure,” he explained, goes back to the 2008 collapse. Yes, the government bailed out the banks, but they let the markets collapse, and as a result Galloway said he got to buy stock in Apple, Amazon, and Netflix for between $8 to $12 per share each. Looking at today’s market, he asked, “Where do you find value right now?” Gen Z already knows the answer—and it’s not in equities.

The Dow and S&P as proxies for wealth

The Dow and the S&P, Galloway argued, are not indicators of economic health. They are “effectively a proxy for how the rich are doing. And spoiler alert—they’re doing really well.” A market correction, Galloway said, would be a feature, not a bug—a recalibration in which housing prices would fall, stocks would become affordable, and capital flows would go back from owners to earners.

New data released this month by Northwestern Mutual found that nearly a third of Gen Z investors have been exposed to prediction markets, and the cohort leads all generations in meme coin activity and usage of speculative platforms like Polymarket. The study attributed the trend to a belief that previous rules of growth and finance broke down creating a generation of investors who suspected market manipulation and tried to seek better returns in new markets. Bloomberg, surveying the same data, called it “financial nihilism.”

But nihilism implies irrationality. What Galloway described at SXSW is the rational engine underneath the behavior. If the traditional system is structurally designed to enrich those who already own assets — and if every crash is backstopped before young buyers can get in at the bottom — then the conventional playbook isn’t just unappealing. It’s a trap. Prediction markets, meme coins, and speculative bets aren’t signs of recklessness. They are the logical response of a generation that has concluded the casino is rigged and decided to find a different one.

Intergenerational wealth transfer

To be sure, not all of it is rational. Gen Z also leads all generations in sports betting participation, online casino usage, and scratch ticket purchases—not as defensibly rational as other alternative investments. And Galloway’s argument overlooks the fact that the humble index fund, boring as it sounds, has still compounded at roughly 10% annually over the long run, through every bailout and moral hazard Galloway has catalogued.

Still, Galloway is right that the intergenerational wealth transfer is real, that bailouts produce moral hazard, and that young people have been handed an objectively harder economic hand than their parents. All of that is true and worth saying loudly.

The moral hazard Galloway decries at the institutional level has been perfectly replicated at the retail level. When banks learn that catastrophic risk-taking carries no real consequence, they take more of it. When a generation watches that dynamic play out across three major crises—with the government each time choosing to protect portfolios over people—they draw the obvious inference: downside risk is something the system absorbs for the already-wealthy, and the only way to break through is to bet big and early. Polymarket is, in a sense, the free-market correction that fiscal and monetary policy has refused to allow.

Galloway has argued separately that for the first time in American history, a 30-year-old is not doing as well economically as their parents were at the same age—and that this intergenerational wealth gap is the root cause of the political and social volatility now convulsing the country. ​

“A certain amount of disruption and drawdowns in the market is a healthy thing,” Galloway said at SXSW, “that transfers and seeds power, leverage, and capital back from owners to earners.”

Galloway is right. They just stopped waiting for the market to do it on its own—and opened a Polymarket tab instead.

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He’s a 45-year-old former Army Special Forces officer. He’s a former politician with ties to far-right conspiracies. He’s also out of a job.

Meet Joe Kent, who up until this morning, was serving as the director of the National Counterterrorism Center. In a now-viral post on X, Kent officially resigned from his role due to a disagreement with how President Donald Trump was handling the U.S. and Israel war with Iran—saying the country should have never been involved in the first place.

Iran “posed no imminent threat to our nation,” he said, adding the war was launched “due to pressure from Israel and its powerful American lobby.”

Kent’s departure from one of the country’s most sensitive intelligence posts marked a dramatic break from a man long considered among Trump’s most committed loyalists.

Kent spent two decades in the military

Kent enlisted in the U.S. Army at age 17, completed Airborne School and the Ranger Indoctrination Program, and earned his Green Beret as a Special Forces Weapons Sergeant in 2003 after arriving at the qualification course just days after the 9/11 attacks. Over 20 years, he rose through the ranks to become a Warrant Officer and was selected for a Special Missions Unit—an elite tier-one designation comparable to Delta Force—deploying across Iraq and Yemen.

He deployed on 11 combat missions primarily in Iraq before retiring in 2018 with six Bronze Stars. He then became a paramilitary officer with the CIA and later served as a counterterrorism advisor to Trump’s 2020 reelection campaign. After leaving the government, he became a fixture on conservative cable shows and podcasts and ran twice for Congress, in 2022 and 2024. He ran in Washington’s 3rd Congressional District and lost both times to Democrat Marie Gluesenkamp Perez. 

Kent’s ties to the Far Right

His political career was defined as much by his extremist associations as his military record. During his 2022 campaign, a political consultant arranged a call that included Nick Fuentes—a white nationalist who participated in the 2017 “Unite the Right” rally in Charlottesville; praised Hitler; and even said Jews hold the U.S. “hostage.” Fuentes later claimed in a livestream he told Kent “I love what you’re doing” and his network actively boosted Kent’s social media following. Kent denied any formal agreement and claimed he was barely aware of who Fuentes was, saying at the time: “The last, whatever, 24, 48 hours is really the biggest, deep-dive I’ve done on him.” He said this despite his chief consultant, Matt Braynard, having attended Fuentes’ America First Political Action Conference that same year. Kent also paid a Proud Boys member for consulting work and collaborated with the founder of the Christian nationalist group Patriot Prayer.

Beyond his associations, Kent spread rhetoric the DCCC described as adjacent to the “Great Replacement Theory,” backing calls to halt all legal immigration for 20 years. He called for a national abortion ban with no exceptions for rape, incest, or the life of the woman, and compared abortion access to slavery and segregation. He also described COVID-19 as a China-designed “vehicle” to suppress freedoms. While he later said he rejected all “racism and bigotry,” he declined during Senate confirmation hearings to distance himself from his 2020 election denialism.

He believes in anti-Interventionism for a personal reason

Kent’s foreign policy worldview is shaped by personal tragedy. His first wife, Navy cryptologist Shannon Smith, was killed by a suicide bomber in Syria in 2019 while aiding in the U.S. fight against ISIS, with her death hardening his skepticism of U.S. foreign intervention. During the chaotic U.S. withdrawal from Afghanistan in 2021, he tore into the defense industry and Washington’s “permanent ruling class,” arguing the wars had been prolonged “on the backs and dead bodies of U.S. soldiers” by people “making money and making their careers at the other end of it.”.

His appointment and subsequent resignation

In February 2025, Trump nominated him to lead the National Counterterrorism Center, praising him as someone who would help “eradicate all terrorism, from the jihadists around the World, to the cartels in our backyard.” He was confirmed in July on a 52-44 vote that split almost entirely along party lines.

The Iran Resignation

That anti-interventionist conviction ultimately ended his tenure in the Trump administration. In his resignation letter, he accused “high-ranking Israeli officials and influential members of the American media” of running a “misinformation campaign” to push the U.S. into conflict, language critics noted drew on antisemitic tropes about Jewish Americans’ political influence. 

It was a striking end for someone Senate Democrats had unanimously opposed at confirmation—every Democrat citing his right-wing ties—and who even one Republican, Sen. Thom Tillis of North Carolina, had voted against.

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

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The U.S. wealth gap has grown so wide, even America’s billionaires can’t help but notice.

In the third quarter of 2025, the top 1% of U.S. households owned a whopping 31.7% of U.S. wealth, according to Federal Reserve data released in January. It’s more or less as much as what the bottom 90% of Americans hold, the widest the gap has been since the Fed started collecting data in 1989. And although headline figures are relatively strong, the U.S. economy doesn’t feel like it’s working for everyone, according to one person who has been treated very well by it. 

“This is 100% completely unsustainable as a society,” Peter Mallouk, the CEO of Creative Planning, a wealth management firm overseeing around $700 billion in assets, wrote on X Monday.

The gap has manifested in everything from asset ownership to how different households spend money, with real repercussions for the economy and even national politics. Mallouk even posted a graph from a December Financial Times article about the country’s widening wealth gap and growing evidence of a K-shaped economy, where households that own assets see their net worth rise while the majority of Americans are unable to build wealth. 

The graph, based on a Moody’s analysis from September, showed that the wealthiest 10% of Americans account for almost half of all consumer spending, a departure from 20 years ago, when spending was more evenly distributed across income groups. 

“Nearly 50% of all consumer spending now comes from the top 10% of earners,” Mallouk wrote. “The bottom 80%? Their share keeps falling.”

Mallouk’s post underscores the growing risk of America’s K-shaped reality. Wealth concentration at the top has accelerated since the pandemic, driven by booming stock markets and uneven wage growth favoring high earners. 

Pay for high and middle-income earners rose 3% last year, compared to 1.5% for low-income households, according to a January report from Bank of America, a reversal from the early pandemic recovery days when low-income households posted much faster wage growth than wealthier peers. Today, most middle and lower-income households are struggling to build enough wealth to stay afloat, unable to muscle their way into homeownership and concerned about their ability to buy basic necessities.

Mallouk isn’t the only wealthy voice sounding the alarm. Last year, Ray Dalio, the billionaire Bridgewater Associates founder, said the widening wealth gap in the U.S. and other rich nations was causing populism to rise and risked creating “irreconcilable differences” in society that democratic order would not be equipped to handle. Some ultrawealthy, like Salesforce CEO Marc Benioff, have also pushed for higher corporate taxes to fund education and housing.

This growing inequality is in spite of a relatively positive state of the U.S. economy, at least according to topline numbers. In addition to a strong stock market, unemployment and GDP growth were both relative success stories last year by historical standards, although the economy might have entered a slowdown toward the end of 2025. Last month, Moody’s chief economist Mark Zandi warned markets and the real economy had become “increasingly disconnected.”

“This is why the economy can look strong in the data while millions of people feel like they’re falling behind,” Mallouk wrote.

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Just a few short years ago, AI was a novel concept generating uncanny, sloppy photos and videos that appeared across your social media feeds. Today, it’s seemingly ubiquitous. New models are popping up almost every month. There’s AI integration in pockets of Hollywood. And even if it’s so far failing to boost your productivity at the office, AI has most likely already appeared in your workplace. That sprawling expansion requires enormous infrastructure investment. And Nvidia CEO Jensen Huang said his company is expecting to deliver those building blocks at a massive scale.

During his keynote address Monday at Nvidia’s GTC conference in San Jose, Huang said the company doubled its demand forecast within the next year. “I see through 2027 at least $1 trillion,” he said. “In fact, we are going to be short. I am certain computing demand will be much higher than that.”

And he’s already preparing for that reality with an unusual incentive to attract top talent and wring more computing power from his workforce: offering engineers AI tokens worth nearly half their salary.

The AI boom is pushing infrastructure investments to new heights. Tech companies are investing a staggering $700 billion into the data center buildout, a sum that rivals the GDP of developed economies like Sweden, and is more than double the total inflation-adjusted cost of the Apollo missions—projects that sent humans to the moon. Nvidia is a critical supplier in that buildout, providing the processors that power AI factories. The $1 trillion demand figure is further proof that the buildout is all gas, no brakes, even as competitors like Advanced Micro Devices (AMD) struggle to close the gap. All of this comes despite looming fears of an AI bubble, as flagged by business leaders like Microsoft CEO Satya Nadella and “Big Short” investor Michael Burry.

Huang made the prediction alongside claims that AI agents could soon run the world, as well as announcements around space-based computing designed to launch AI into orbit, a concept Elon Musk has spotlighted as a potential solution to the energy demands of expanding data centers.

“We are completely resetting and starting the largest buildout of human history,” Huang said. “Most of the world’s industries building AI factories, building chip plants, building computer plants are represented here today.”

The company’s recent earnings reports have added credibility to Huang’s claims. Last month, Nvidia posted $215.9 billion in revenue for fiscal 2026, up 65% from a year ago, the highest annual result ever. Data center revenue alone rose 75% from a year ago, reaching $62.3 billion.

AI tokens: the future of pay?

As business leaders aim to harness AI to boost worker productivity, Huang offered a glimpse at how Nvidia plans to operationalize that ambition: paying engineers in tokens—the currency of AI—to amplify their output. 

“I could totally imagine in the future every single engineer in our company will need an annual token budget,” he said. “They’re going to make a few 100,000 a year as their base pay. I’m going to give them probably half of that on top of it as tokens so that they could be amplified 10 times.”

Tokens are the basic units of data or words that AI models use to process language and recognize patterns, making them critical to the future of AI deployment. AI company OpenAI estimates that one token is equal to approximately four characters, with a single one-to-two sentence prompt requiring about 30 tokens. “Fortune Magazine,” for example, may be broken down into five tokens: “For” “tune” “Mag” “az” “ine.” 

At the allowance levels Huang described, engineers would have access to billions of tokens annually, unleashing a torrent of compute power. In Huang’s scenario, tokens would be an added employment perk for engineers at his firm, arming them with the power needed to conduct deep research for the company.

The Nvidia CEO said other tech firms will quickly follow suit and use tokens as a recruiting tool to attract top industry talent. 

“It is now one of the recruiting tools in Silicon Valley: how many tokens come along with my job,” he said. “The reason for that is very clear because every engineer that has access to tokens will be more productive.”

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Hello and welcome to Eye on AI. In this edition…Nvidia sees $1 trillion in AI chip sales by the end of 2027…Meta delays the debut of its latest AI model (again)…Moonshot AI develops a new architecture for large neural networks…and why we may soon be worrying about ‘moral crumple zones.’

Since the advent of ChatGPT in November 2022, one of the professions that people often claim is now toast is consulting. After all, what is it that consultants do? They advise companies on strategy; they help them restructure their businesses to create new organizational designs and processes, often with the help of technology from third-party vendors; and they act as providers of outsourced services, or at least conduits to outsourced services, such as customer support or software development. Well, a frontier AI model can offer strategic advice. It can also advise on how to restructure an organization and about which software to buy. AI agents can actually help stitch some of those systems together too. Finally, AI agents can also now handle coding and customer support. So it’s lights out for consultants, right?

Well, it hasn’t turned out that way so far. AI companies have discovered that they need consultants, or “systems integrators” as they are sometimes called in the software world, to help them sell their AI agents, as a story in last week’s Wall Street Journal highlighted. The reason is that using AI agents effectively often requires quite a lot of organizational transformation—cleaning up data, redesigning workflows, and thinking about how to redeploy human workers—as well as strategic thinking about how AI might be used to provide a real competitive advantage.

The AI model vendors have found they don’t have the resources to provide this kind of advice at scale—OpenAI only has about 70 so-called “forward deployed engineers” who go on site with customers to help them implement solutions based on their AI models; Anthropic is thought to have a similar number. And while it is possible that AI itself could serve this function, AI still suffers from a trust deficit—most boards would still rather put their faith in advice from McKinsey or BCG than ChatGPT. (A more cynical take: CEOs still like to use consultants to justify their own decisions to boards, as well as to have someone else to blame if it all goes wrong.)

OpenAI has formed what it calls its Frontier Alliance with McKinsey, Boston Consulting Group, Capgemini, and Accenture to help clients use its Frontier platform for building and managing AI agents. (You can read my coverage of that announcement here.) Anthropic has struck similar deals with Deloitte, Accenture, and Cognizant and is reportedly in talks with private equity groups, such as Blackstone, to implement Claude-based solutions in their portfolio companies.

I recently caught up with Capgemini’s Chief Strategy Officer Fernando Alvarez to talk about how his firm is viewing the future of consulting in an AI world.

Domain expertise matters

First, Alvarez says that while every client wants to use AI agents, they also recognize the need to govern those agents, make sure there is adequate cybersecurity around them, and ensure they can interact with legacy systems and fragmented data sources. Advising clients on all of that stuff and often helping them build it has been Capgemini’s bread and butter. He says clients still want Capgemini to provide these services. They aren’t ready to hand it off to AI.

The other big selling point for the consulting firms, Alvarez says, is deep industry and domain expertise. The frontier AI labs don’t have the expertise in how to optimize a pharmaceutical manufacturing plant or the best way to run logistics for a fast-fashion retailer. Consulting firms do. And that makes a difference when trying to use AI agent successfully. Alvarez says the conversations clients want to have are not about how many agents you can spin up or how you orchestrate them. “The conversation is, do you have the domain expertise to understand my problem?” he says.

‘People want the cake, not the recipe’

That doesn’t mean that Capgemini itself isn’t using AI to help serve clients. Alvarez says the big shift that Capgemini, as well as some competitors such as Accenture, are trying to make is to move from selling technology and advice, to selling outcomes. In this model, the consulting firm takes on the risk of trying to figure out how to deliver, say, better customer support, whether that is through business process outsourcing to humans in lower wage countries, such as the Philippines or India, or through AI agents.

“At the end, people want the cake,” he says—not a tour of the ingredients or the recipe. The new pitch boils down to a simple proposition: “Here is the problem. Here is the risk I’m willing to take, and this is the outcome I give you.” The client pays for the outcome: improved KPIs like successful customer issue resolutions and improved net promoter scores. The difference too is that the consultants in this model charge for the outcome, not by the number of people deployed on a project as some consultants have traditionally billed.

Alvarez says that AI is also enabling Capgemini and other consulting firms to move into market segments, such as midmarket companies, that it couldn’t service previously because the economics didn’t make sense. The engagements often required more staff and cost than the client was willing to pay for. But now AI has lowered those staffing and cost requirements, meaning that Capgemini can offer a solution at a price point that is attractive to midmarket companies while maintaining a decent enough profit margin. 

Perhaps the biggest challenge for consulting firms, though, is retraining their own people to work alongside AI agents. “Some people will make it, some people will not,” Alvarez says.

For all the disruption, Alvarez is unmistakably energized. He calls this moment “probably the best opportunity I’ve seen in the history of technology.” The question now is whether Capgemini and other consultants can rewire themselves as fast as the technology demands—which is, of course, exactly what they are advising their clients to do.

With that, here’s more AI news.

Jeremy Kahn
jeremy.kahn@fortune.com
@jeremyakahn

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The AI boom helped make the world’s 500 wealthiest people $2.2 trillion richer in 2025. To Bill Gurley, one of Silicon Valley’s sage investors and a general partner at Benchmark, those astronomical gains in wealth are a sign of an inflating AI bubble that is bound to pop.

The AI boom is following the pattern of other eras of technological growth, in which early gains for some tech firms have sparked a wave of spending that will ultimately be unsustainable for dozens of companies, Gurley said in an CNBC interview on Monday. Companies will soon have to curtail their spending and revise their valuations, or otherwise risk failing.

“When people get rich quick, a whole bunch of people come in and want to get rich too, and that’s why we end up with bubbles,” Gurley said. “One day we’re going to have an AI reset, because waves create bubbles, because interlopers come in.”

The venture capitalist added that investors should “start gobbling [software-as-a-service stocks] up” following the reset. The sector has been hit particularly hard by AI disruptions as a result of AI agents being able to automate workflows more cheaply than existing SaaS tools. Salesforce and ServiceNow stocks have lost more than 20% of their respective value since the start of 2026. 

Signs of AI strain

Gurley said the exorbitant amounts of money being spent on AI are a warning sign for a potential bubble burst.

“One day, I just think we trip and run out of money on those things,” he said. “I do think that moment stands in front of us.”

This wave of AI spending is set to exceed the capital expenditure-to-sales ratio from the dot-com era as a result of hyperscalers pouring money into data centers used to train and deploy vast large language models and other AI systems, according to Morgan Stanley analyst Todd Castagno. In a note to clients last month, Castagno said capex-to-sales will reach 34% this year and 37% in 2028, dwarfing the 32% recording near the turn of the century. That spending, about $2 trillion between 2026 and 2028, would represent 40% of the Russell 1000.

Hyperscalers may push this ratio even higher, to 38% this year and 45% by 2028, if they continue to finance data centers with leases, the note said. Indeed. Amazon, Meta, Alphabet, Microsoft, and Oracle amassed nearly $1 trillion in total undisclosed future lease commitments, or leases for data centers that have yet to be built, according to a February report from Moody’s Ratings. About $662 billion of that total is for leases that have yet to commence, which companies are not required to recognize as liabilities on their balance sheets under generally accepted accounting principles.

These infrastructure buildouts are often in partnership with startups like OpenAI and Anthropic, which have fuelled these ambitious data center investments. Last month HSBC estimated OpenAI would need an additional $207 billion in funding by 2030 in order to afford its cloud computer rental from Microsoft and Amazon. Analysts estimated $280 billion in total cash burn by 2030. Anthropic’s CFO said in a recent court filing the company spent more than $10 billion training models that generated half that total in cumulative revenue.

Gurley compared those figures with Uber’s annual burn rate of $2 billion when he was involved in the company—a sum he said gave him “high anxiety.” (Benchmark was an early investor in Uber, and Gurley served on the company’s board of directors at the time of ex-CEO Travis Kalanick’s 2017 ousting.)

“God bless them,” Gurley said of OpenAI and Anthropic. “It’s a scary way to run a company.”

AI’s impact on labor

AI companies’ astronomical spending has been accompanied with bold claims about the future of the labor market, with ServiceNow CEO Bill McDermott anticipating an eventual 30% unemployment rate for Gen Z college graduates as a result of the technology

Tech companies have already attributed mass layoffs to AI, including Oracle, which is reportedly reducing thousands of roles, touting efficiencies of its AI tools. Meta will lay off about 20% of its workforce following heavy AI spending, according to a Reuters report. Gurley said these claims and attributing mass layoffs to AI productivity is overdone.

“I’m not that big of a doomer, he said. “I think these waves come, and especially with AI, there have been a lot of people pumping kind of miracles into it … .They get this kind of apocalyptic view. We’ve had technology disruption before.”

Gurley noted CEOs announcing layoffs are going to blame AI, rather than take responsibility for “being bloated” or making tactical missteps. Analysts say companies like Oracle are slashing headcounts as a way to conserve cash following massive waves of investment. To Gurley, these cuts will become the new normal.

“We’re going to see a ton of these announcements,” he said. “But it’s a normal thing that we’ve been through before.”

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Clad in his trademark leather jacket, Nvidia CEO Jensen Huang took the stage yesterday at San Jose’s SAP Center before nearly 20,000 people at the company’s annual GTC conference, known in recent years as the Super Bowl of AI.

Once again, Huang essentially declared a blowout, forecasting a staggering $1 trillion in orders for Nvidia’s most sophisticated AI chips through 2027, driven by the explosion of AI infrastructure now being built around the world.

Yet for someone whose company has become the world’s most valuable—with a roughly $4 trillion market cap—by powering the global AI buildout, Huang has somehow avoided the kind of public criticism that has been leveled at other prominent AI CEOs.

It takes only a cursory glance at social media to find posts calling OpenAI CEO Sam Altman “evil,” while companies like Anthropic, Meta, and Google increasingly face criticism over AI’s risks—from job losses and copyright lawsuits to misinformation and the growing push to deploy AI in military systems.

Nvidia’s CEO, by contrast, remains largely celebrated as the engineer-builder behind the boom. That’s been true even though the massive AI data centers now rising across the country and generating a good deal of local opposition are packed with Nvidia chips.

In fact, every major move in AI—from chatbots and agents to applications in the workplace, schools, and the military—runs on Nvidia hardware, software, and systems. Nvidia has also invested billions to support the AI ecosystem, partnering with both OpenAI and Anthropic, as well as funding data center companies and AI startups.

So why isn’t Huang—and Nvidia as a whole—a target of the AI backlash?

The answer is that the companies supplying the “picks and shovels” of technological booms rarely attract the same scrutiny as the miners. Oil companies drew criticism during the fossil fuel era, not the manufacturers of drilling equipment. Railroad barons faced public backlash, not the companies supplying steel rails. And in the internet era, cloud providers like Amazon Web Services powered companies such as Airbnb and Uber that reshaped entire industries—yet the criticism largely focused on the platforms, not the infrastructure behind them.

Still, Nvidia made it clear at GTC that it is positioning itself not just as a chipmaker but as the provider of entire AI computing systems powering the new “inference” phase of AI. (Inference is about powering AI outputs, not just training, and it will require an enormous new round of infrastructure investment.) That ambition goes beyond Nvidia’s traditional “picks and shovels” role. These days, Nvidia is increasingly trying to control the entire swath of systems, software and platforms that power the AI economy. 

The centerpiece of Huang’s keynote was the launch of the company’s Vera Rubin platform, which combines multiple chips and system components designed to run large AI models and “agentic AI” systems. The platform includes seven new chips and several rack-scale systems intended to power extremely large AI clusters containing hundreds of thousands of GPUs.

Nvidia also introduced NemoClaw, an open-source platform for building enterprise AI agents, allowing companies to create agents, connect them to corporate data, and deploy them on Nvidia hardware.

At the same time, Nvidia is continuing to invest aggressively across the AI ecosystem. The company has poured billions into dozens of AI startups over the past year. Most recently it invested $2 billion in AI cloud company Nebius and is backing former OpenAI CTO Mira Murati’s new venture, Thinking Machines, with plans for more than 1 gigawatt of Nvidia-powered compute capacity.

The company is also continuing its push into autonomous vehicles, where Nvidia chips and software platforms are increasingly being adopted by carmakers building self-driving systems.

Finally, Huang used GTC to promote what he called AI’s “five-layer cake.” The AI economy, he argued, depends on five layers—energy, chips, infrastructure, models, and applications—all of which must scale together to support the massive buildout now underway. Nvidia, not coincidentally, sits squarely in the middle of that stack—connecting most of those layers together.

For now, Nvidia still benefits from the traditional insulation of a picks-and-shovels supplier. But as the sprawling AI data centers rising across the country fill with Nvidia hardware—and as the company pushes deeper into the systems powering them—the company may find itself far more exposed to the debate over AI’s consequences.

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