The stock plunged 25%, the worst day in the century-old company’s history.

International Business Machines, a company that helped send humans to the moon, worked on America’s Social Security system and built a supercomputer that beat contestants at “Jeopardy!” is reckoning with the punishing realities of the AI boom. 

It is one of the first big corporations to confront the costs and disruptions of the fast-evolving technology—and have to explain itself to anxious investors. Even as IBM helps its customers adapt to the AI age, it was caught flat-footed by it.

The news has sparked discussions on Wall Street about whether IBM should be broken apart or an activist investor will come hunting for Big Blue. It isn’t clear how much guidance the company will be able to give investors when it reports full quarterly results next week, one of the people said.

Arvind Krishna, who started as a software engineer at IBM in 1990, took over as CEO in 2020. Mandel Ngan/Agence France-Presse/Getty Images

Krishna “needs to get this straightened out quickly because the last thing any 63-year-old CEO can afford is being stigmatized as a spotty executor that is responsible for historic selloffs,” said Don Bilson, head of event-driven research at Gordon Haskett, in a note to clients this week. 

IBM declined to comment. Krishna promised to go into deeper detail when he hosts a conference call next Wednesday. “We have conviction in the strength of our portfolio and the strategic transformation of our business,” the IBM boss wrote in his letter.

Fears that AI tools from companies such as Anthropic and OpenAI would replace software have rattled the shares of Salesforce, Workday and Snowflake over the last year. IBM presents a different problem. Its warning this week showed that investments in AI infrastructure such as memory and new cybersecurity concerns are displacing spending on hardware, too.

Squeezed between server orders and AI buildouts, some of IBM’s customers now treat the tech giant as discretionary spending, said Daniel Morgan, a portfolio manager and analyst at Synovus Trust. 

“I think you might see some, ‘Hey, we’ll hold off on this for a couple quarters…we don’t need to upgrade to the new mainframe right now,’” Morgan said. “That’s kind of hurting them.” 

Missing out

Unlike other AI-infrastructure providers and cloud companies such as Nvidia, Google and Oracle that rent computing capacity, sell chips and offer networking hardware, IBM sells hardware and software systems that corporate customers install at their own sites. Its customer base includes leading financial-services firms and retailers.

The company’s top leaders have discussed whether it has become too reliant on large accounts that come with inconsistent deals and upgrade cycles that they can push off in lean times, people familiar with the matter said. They have talked about the need to diversify and court a wider range of customers, such as medium-sized companies, but it would take time to see if such an approach paid off, one of the people said.

Board members will be watching to see if Krishna’s team comes together, because this will be a test of his leadership. Some also are concerned that the company might swing to a more conservative stance that could hamper growth. The board is expected to meet again in late July.

One IBM alum, who now runs his own AI company, praised Krishna for his candor and said the market reaction was overblown. 

“The punishment doesn’t fit the crime,” Debanjan Saha, CEO of DataRobot, wrote on LinkedIn. “This selloff wasn’t about a quarter. It was the market repricing a question: can a 115-year-old enterprise company lead the agentic era, or merely survive it?” 

IBM has reinvented itself many times, transitioning from tabulators and time clocks in its earliest days to personal computers, mainframes and supercomputers and later AI and hybrid cloud computing. 

Saha noted that the company had survived antitrust battles, the PC wars and the rise of the internet. “Every obituary was premature,” he wrote. “This one will be too.”

Krishna’s era 

Krishna, who joined IBM in 1990 as a software engineer, was appointed in 2020 to succeed CEO Ginni Rometty. The selection of an executive who had been senior vice president for cloud and cognitive software signaled where the company was headed. 

IBM bought open-source software company Red Hat for $34 billion, a deal Krishna helped integrate and would become a major growth driver. Software accounted for about $30 billion of IBM’s $67.5 billion in revenue last year.

IBM further sharpened its focus on the cloud-computing market with investments in hybrid cloud computing software and quantum computing. It spun off IT-outsourcing business Kyndryl to further simplify the business and bought cloud-software company HashiCorp.

Krishna told people last year that he expected AI would replace around half of the work in many workflows, increasing productivity and job reallocations. IBM has trimmed thousands of roles from its 260,000-person workforce and has hosted reskilling programming for its own staffers.

While Wall Street was initially skeptical of Krishna, his strategy started to bear fruit. As recently as last year, the company’s army of consultants had built up billions of dollars of bookings helping customers navigate how generative AI would change their business, and its software business was growing.

In April, IBM struck a first-of-its-kind settlement with the federal government, paying more than $17 million related to its diversity practices. The next month, its stock popped when the Trump administration awarded the company $1 billion in grants to boost quantum computing. IBM said it would invest $1 billion of its own cash alongside the award to set up a specialized quantum-chip manufacturing facility.

The stock’s drop this week has pushed its market capitalization below $200 billion, leaving it dwarfed by companies such as Broadcom ($1.8 trillion) or AMD ($800 billion) that were once seen as small suppliers to giants like IBM.

IBM and its advisers are aware that this week’s bad news could make it vulnerable to an activist investor showing up in its shares or pushing it to examine potentially splitting the company up, according to people familiar with the matter. 

Gary Cohn, vice chairman of IBM, said changes in corporate technology budgets might be temporary. Aaron Schwartz/Bloomberg News

The quarterly warning was especially unusual coming from IBM, an American blue chip that held a reputation among investors for results that are steady, if unspectacular. For decades, IBM chief executives didn’t even participate on earnings conference calls, leaving such matters to the company’s financial executives.

Board members are aware that the near-term is likely to be messy and that an impatient Wall Street is unlikely to tolerate two or three more quarters of underperformance, according to the people familiar with the board discussions. 

Gary Cohn, who has been IBM’s vice chairman since 2021, suggested Wednesday on CNBC that the change in companies’ spending on technology products and services might be temporary. While IT budgets set months ago have been disrupted by high spending on computing, companies are now starting to question the return on investment. Some, Cohn said, are asking whether they should go back to reinvesting in proven enterprise infrastructure.

Asked about the decision to warn about the poor results, Cohn said, “Arvind took it upon himself to say, ‘Look, I want to be transparent with the world. I don’t want to surprise them.’”

In one of the most remarkable examples of state capitalism in recent memory, the U.S. government became the chipmaker’s largest shareholder later that month when it converted $9 billion in federal grants into a 10% stake in the company.

Nearly a year later, Trump announced via Truth Social post that Apple would begin using Intel-made chips for some of its products, sending Intel shares to record trading highs. “I decided to help Intel because we need to design and build our Chips right here in America,” Trump wrote. 

President Trump, with Apple CEO Tim Cook, presents Apple's announcement of a $100 billion investment in U.S. manufacturing last August. jonathan ernst/Reuters

Apple plans to have Intel make chips for both Mac laptops and iPhones, according to a person familiar with the negotiations. The connection between the tariff talks and a potential deal between Apple and Intel has not been previously reported.  

Intel’s shares have more than quadrupled since Lip-Bu Tan took over as its CEO in March 2025, promising to cut spending, reinvigorate its product lines and attract game-changing customers to its contract manufacturing business, or foundry. 

The company’s stunning resurgence is partly good luck: the AI boom recently entered a new phase that demands huge quantities of the computer chips known as CPUs, Intel’s specialty. But the Trump administration’s financial and strategic patronage has been the more crucial factor.

The administration has taken a hands-on approach to the company, twisting the arms of major potential customers and partners including Apple, Nvidia and Elon Musk’s SpaceX, all of which have signed deals with Intel since the government stake was announced. 

Tan has been visiting Washington about once a month to meet with officials from the Commerce Department, Intel and U.S. government officials said. Tan also talks on the phone regularly with Lutnick, updating him on customer relationships and business conditions.

Bill Frauenhofer, the veteran semiconductor industry investment banker who serves as the administration’s chips czar, is even more in the weeds of Intel’s business. He gets a briefing from Chief Financial Officer David Zinsner every quarter and members of his staff meet regularly with Intel executives in Washington and at its Santa Clara, Calif., headquarters, keeping tabs on the progress of new manufacturing technologies. 

Even as big questions remain about Intel’s ability to deliver long-term consistency to its customers and regain its mantle of chipmaking innovation, the Trump administration’s unprecedented involvement in helping to steer the strategy of a private-sector tech company underscores the power of government to create national champions in strategically vital industries. 

“From a technology perspective, it really seems like Intel is gaining credibility and confidence,” said Jacob Feldgoise, a senior research analyst at Georgetown University’s Center for Security and Emerging Technology. “With each new customer commitment and each new fabrication process they unveil, the signs are looking better and better.”

One of the original firms that gave Silicon Valley its name, Intel dominated the global semiconductor industry from the 1980s through the early 2000s, designing and making the chips that powered the PC and early internet eras. The company fell behind during the rise of the mobile internet and ceded ground to rivals making processors for smartphones, data center servers and other devices in recent years.

Today, the company consists of two main businesses: its product segment, which designs and sells its own chips, mainly CPUs for personal computers; and its foundry, which manufactures chips in the U.S., Ireland, Israel and Malaysia, both for Intel and for other designers. 

An Intel chip Hannibal Hanschke/EPA/Shutterstock

The seeds of Intel’s government-supported renaissance were planted last summer, when Tom Cotton, the conservative U.S. senator from Arkansas, publicly criticized Tan as being compromised by what he described as uncomfortably close ties to China. 

Tan for decades had invested in China’s tech sector through his venture fund, Walden International, and counted Chinese tech firms and government agencies as customers when he was CEO of Cadence Design Systems, a semiconductor software company. 

Cotton’s criticism caught the president’s attention. In early August, Trump called for Tan to resign in a social-media post. The company sprang into damage-control mode, and Tan was soon sitting in the Oval Office, trying to persuade Trump that he was not a Chinese spy. 

The charm offensive worked. Trump took a liking to Tan, whom he views as a “winner,” according to people familiar with the president’s views. After meeting with Tan at the White House, Trump proposed a government stake. 

“Intel has been left behind,” Trump said at the time, and vowed to help the company recover its bearings. 

The first fruits of Trump’s matchmaking appeared in September, when Nvidia announced it would invest $5 billion in Intel and buy its custom data center chips. Nvidia CEO Jensen Huang called the deal a “historic” partnership.

In April, Musk followed suit, announcing that Intel would join his ambitious Terafab manufacturing initiative to help “design, fabricate, and package ultra-high-performance chips at scale.”

The Trump administration’s heavy hand in deals with Apple, Nvidia and others could set a bad precedent, especially if Intel fails to fix its foundry business, said Scott Lincicome, a lawyer who specializes in trade and industrial policy at the libertarian-leaning Cato Institute. “Being the government’s darling only works as long as you’re doing well,” Lincicome said. “The risk for Tan is that if things start going south, politicians work on short timelines.” 

While the administration’s boosterism has played a key role in improving Intel’s fortunes, Tan has also instituted sweeping changes and made key hires that have helped the company sharpen its focus and instill confidence both internally and among potential partners, according to current and former Intel executives, government officials and customers. 

In September, Tan overhauled Intel’s reporting structure and established a new Central Engineering Group, hiring Srinivasan Iyengar, the top silicon engineer at Cadence, to consolidate custom chip design efforts under one team. 

Tan, shown here after a White House meeting last August, has made changes across Intel. Alex Wroblewski/Bloomberg News

In their meetings with Intel executives, Commerce officials—who want more chipmaking on U.S. soil, rather than in Asian countries such as Taiwan, South Korea, Japan and China — have expressed keen interest in the foundry business. Government officials are closely tracking the progress of the firm’s newest manufacturing initiatives. 

The administration is also pushing Intel to expand capacity at a New Mexico plant that produces what’s known as advanced packaging, or arrays of smaller chiplets that can be combined to function as a single custom semiconductor, according to government and company officials. 

Intel and the government both view advanced packaging as the company’s best chance to compete with rival Taiwan Semiconductor Manufacturing, the world’s biggest fabricator of advanced AI chips, officials said. 

In a January earnings call, Zinsner, the CFO, predicted that the foundry business would start seeing billions of dollars in revenue in the near-term from advanced packaging, a prospect he called “way more exciting than even I had expected.”

Tan has been on a hiring spree, poaching executives from competitors including Samsung and SK Hynix, aimed at making Intel’s foundry—which reported $10.4 billion in operating losses over the last four fiscal quarters—more competitive with rivals like TSMC. In recent years, outside customers have largely lost confidence in Intel Foundry’s ability to produce reliable quantities of usable silicon wafers. 

Tan has also given more responsibility to Naga Chandrasekaran, a Ph.D engineer with a deep technical knowledge of semiconductors who has over the past year become the foundry’s most important salesman, people inside Intel say. 

The partnerships with the Trump administration and others have provided another benefit: cash. Intel executives say that without the immediate infusion of capital that came from the government’s conversion of $9 billion in federal grants into equity—along with the $5 billion from Nvidia and $2 billion that Japanese investment firm SoftBank injected into Intel in late August—the company would have had to significantly cut capital expenditures over the past year.

Instead, Intel has kept capex spending relatively consistent over the past year, and shifted its spending, at Tan’s direction, largely from building new chip plants to buying precision fabrication tools and other equipment, allowing the company to increase production of high-selling products, such as laptop and data-center CPUs.

In April, the company reported that surging demand for CPUs had driven quarterly sales in its important data-center segment up 22% year-over-year, to $5.1 billion—although the company still reported a net loss of $3.7 billion for the quarter. 

Alphabet’s Google Cloud unit announced in April it was placing a large order of Intel’s Xeon CPUs to power its data centers for so-called agentic workloads, or the type of computing required by large enterprises using AI tools. 

Google says that it has grown more confident in Intel because of the changes Tan has made in how it responds to customer needs and customization requests. 

“When they listen to our feedback and execute against it, that makes us even more excited to partner with them,” said Mark Lohmeyer, vice president and general manager of AI and Computing Infrastructure at Google Cloud, in an interview.

This past week, Palantir PLTR -1.74%decrease; down pointing triangle released a dense white paper—entitled: “Institutional Sovereignty in the Age of AI”—that laid out 15 steps companies and governments could take to protect themselves from the likes of OpenAI and Anthropic.

That put polish on Karp’s more emotional TV appearance the week before, when he declared that “something has gone completely wrong” in the relationship between AI labs and their customers. Speaking at a frenetic pace, the tech company boss rattled on about AI labs hyping their capabilities, overcharging for tokens, or units of AI use, all while insisting that he wasn’t throwing shade at rivals while doing just that. 

Karp, who counts some of the largest U.S. companies as well as the government as clients, added, “at every single enterprise I deal with, these people are livid, they’re like, ‘I am paying for tokens that create no value.’ ” 

Karp’s I’m-mad-as-hell-and-I’m-not-going-to-take-it-anymore moment is perhaps the best illustration yet of the battle brewing between the tech establishment and the AI upstarts. That tension is playing out in politics as both parties weigh what role the government should play in overseeing AI, in geopolitics as the U.S. and China fight for tactical edges, and society writ large as the prospect of technological disruption threatens jobs and ways of life.

Karp’s lengthy CNBC appearance (nearly 20 minutes, during which anchor Becky Quick interrupted to say: “You sound pretty angry,”) ignited debate throughout the tech industry. Former White House AI czar David Sacks, a longtime critic of Anthropic, amplified Karp’s argument. 

A data center in Ashburn, Va. Leah Millis/Reuters

“Anthropic has launched Claude Science, Claude Security, Claude Legal, and of course Claude Code—each expanding into categories previously served by companies building on top of their models,” Sacks posted on social media. “The pattern is consistent: Watch where value is being created, then move in directly. Dominate the model layer, then use that position to capture the most lucrative verticals.”

The big question now being spoken out loud is where do traditional businesses fit in an AI world? Who captures the value created by AI: the companies deploying it or the labs developing the actual AI? 

Neither OpenAI nor Anthropic have directly responded to Karp’s criticisms. Both have policies that say enterprise customer data aren’t used for training their models. One AI lab insider sniffed: “We would be fools reacting to Karpian theatrics; he does well talking his own book.”

Within tech circles, it is, admittedly, complicated. So many frenemies. So many deals among rivals. Last month, for example, the Trump administration put a hold on Anthropic’s ability to export its new powerful models after Amazon.com Chief Executive Andy Jassy quietly raised concerns. Amazon is an investor in Anthropic and has benefited from the AI lab using its special chips. 

Karp, too, has an angle. (He acknowledged as much.) Palantir has a product that essentially rides atop the so-called foundation model, bridging the gap between the AI and a customer. It’s a good business for the company. 

Still, Karp isn’t alone in voicing concerns in recent weeks about the imbalance between businesses and AI labs. Soaring costs have led some companies to re-evaluate how the technology is being used. 

<a href="http://Amazon.com" rel="nofollow">Amazon.com</a> CEO Andy Jassy Brendan McDermid/Reuters

Microsoft CEO Satya Nadella wrote an essay on that topic and has been making the rounds talking about his concerns that companies be able to retain the learnings that come from using AI models. “If you’re just a consumer of a foundation model, then I’m not sure how you can retain enterprise value, let alone create,” Nadella said this month during an appearance at Stanford University. 

Nobody accused Nadella of having a meltdown like they did with Karp. 

Microsoft has been a big backer of OpenAI but is struggling to remain on the forefront of the fast-moving technology, which threatens to unseat software makers. On Thursday, for example, Microsoft and IBM shares were initially rocked by a media report that coffee company Starbucks is using AI to replace software it buys from those tech companies. 

By the time it takes to drink a cup of coffee, it seems the winners and losers of the new AI era can change. It is yet another sign that no one knows how the technology, which some rank up there with the advent of electricity, will remake things. What is clear is that the big tech players of today aren’t necessarily guaranteed to be the winners of tomorrow. 

But they aren’t giving up, as evident by Karp’s campaign. 

This past week wound down with Meta Platforms announcing a new version of its own AI model that included a paid tier.

Meta CEO Mark Zuckerberg, in an interview with Bloomberg News, made it clear he sees an opening to compete on price. “The pricing from some of the other labs is very extreme and has very high margins,” he was quoted as saying. “We think that there’s a real ability to be able to offer frontier or very high-level intelligence at a much more affordable cost.” 

Then there are the expected IPOs of Anthropic and OpenAI, which will likely rank the AI labs among the most valuable companies in the world. Their central role in AI is increasingly worrisome to many across the political spectrum. 

Karp’s attacks add to the list of those speaking out. 

So, was Karp angry? 

“No,” he said. “This is the voice of American business that is being channeled through me.”

These investments have grown in popularity because people with savings prefer alternatives to China’s slowing economy, shaky housing market and accumulating local government debt.

The basket of regulations unveiled this month also imposes additional restrictions on Chinese engineers working abroad and bans unauthorized transfers of data, technology, goods or services to foreign companies.

That follows Beijing’s order for Meta, the owner of Facebook, to unwind its $2.5 billion purchase of the artificial intelligence start-up Manus. After originating in China, Manus transferred operations and staff to Singapore ahead of being acquired. China wants to prevent other companies from making similar moves.

The Communist Party wants to keep as much money, technology and talent as possible locked inside its borders. In addition to erecting a fire wall against America in the AI race, the goal is to boost domestic consumption. But the policy exposes fundamental weakness in their system and risks deepening Beijing’s global isolation.

It will also intensify the ire of citizens who cannot fully benefit from today’s technological gold rush.

This is what insecure leaders do in autocratic systems. Their impulse is to exert more control over every aspect of life: what to read, where to travel, the size of families and so on.

The Chinese people are inveterate savers. The average household saves around one-third of its disposable income, compared with under 4 percent among Americans, and they’re looking for somewhere productive to park that money. Overseas insurance policies have become so popular on the mainland that selling them is a coveted first job for graduates from prestigious Chinese and Hong Kong universities.

After the new limits take effect on July 1, enterprising Chinese nationals will seek more surreptitious ways to get their money out of the country. These may not generate the same returns on investment. The biggest losers will be Chinese entrepreneurs.

Tech start-ups look overseas for seed money. By cutting off access to outside capital and global financial networks, the government risks stifling the innovation it is so desperate to encourage. Economies flourish when money and talent are allowed to gravitate toward the best ideas.

Serious though they might appear, those political challenges likely won’t be lasting. They might even prove to be much less thorny in the long term than those of its rival, OpenAI, as both companies gear up for IPOs.

Much of the concern that has led to curbs on Anthropic merely reflects how slow the political sphere has been to adapt to the rapid advance of artificial intelligence. There aren’t many laws in place that regulate AI, leaving the government to scramble for responses when perceived threats emerge.

Some of those responses have been ham-handed. When the Defense Department designated Anthropic a supply-chain risk, the administration relied on statutes intended to prevent foreign adversaries from involvement in U.S. defense procurement.

Anthropic, which is helmed by Chief Executive Officer Dario Amodei, filed two lawsuits to block the designation, and it looks so far as though the government is likely to prevail in at least one of them, allowing it to continue excluding Anthropic from defense contracts.

That will certainly limit the market for Anthropic’s products. But the company’s exclusion from defense deals won’t take a huge financial toll. Defense, after all, is hardly the company’s bread and butter.

The bigger danger for the company is the reputational hit that could come with being seen as a security risk. That could theoretically scare away corporate customers that supply around 80% of its revenue.

Viewed in another way, though, the dustup could work to Anthropic’s reputational advantage.

The company’s beef with the Defense Department has been over its refusal to allow its models’ use in fully autonomous weapons and for mass surveillance. Even as ethical concerns are set aside, it might be more dangerous for Anthropic’s reputation among corporate customers to be associated with botched military operations and spying on ordinary people than being branded a risk by the Pentagon.

App download patterns give some support to the notion that users support Anthropic’s position. Uninstalls of OpenAI’s ChatGPT surged early this year following news that the company was negotiating its own deal with the Pentagon, according to the data provider Sensor Tower, even though OpenAI has said it places limits on how the military can use its technology. Moreover, more users installed Anthropic’s Claude than ChatGPT in the days after the Pentagon deemed Anthropic a security risk—a reversal of ChatGPT’s usual lead.

The Defense Department has plenty of reasons to mend fences with Anthropic. Anthropic has made it clear that it won’t relent on limits on its models’ use. That leaves the Pentagon with two options: find a way forward with Anthropic, or simply don’t use its tools. The latter option would deprive the department of some of the most cutting-edge AI models in the world. At some stage—possibly when political winds change—a resolution seems likely.

The Trump administration’s other crackdown on Anthropic also has been short-lived. The administration used the Commerce Department’s export-control authority to ban foreigners, including Anthropic’s own employees, from using its technology last month. That led Anthropic to cut off all access to its most-advanced Fable 5 and Mythos 5 models.

The temperature there has already cooled. The administration first allowed Anthropic to give access to a select group of trusted customers before giving it the go-ahead for wider access late last month after it addressed cybersecurity concerns.

That episode was more a testament to the Anthropic’s models’ abilities than any flaw that could put it in lasting political jeopardy. As BMO Capital Markets analyst Brian Pitz recently said in a note, the restriction “underscores the power of Anthropic’s models and their current leadership position.”

Also working in Anthropic’s favor is that its risks in the longer term look less acute than its nearest competitor’s.

OpenAI which, like Anthropic, is pursuing an IPO that could value it above $1 trillion, is more of a mass-market pIayer. While Anthropic gets almost all of its revenue from corporate customers and is the market-share leader in that area, OpenAI caters to a larger swath of users. OpenAI’s ChatGPT shot to more than a billion monthly active users in May, according to Sensor Tower, well above any other competitor and multiples of Anthropic’s user base.

But OpenAI’s wide reach is a political liability as much as a commercial asset. It exposes OpenAI to the kind of social-impact scrutiny that has dogged Meta Platforms and other social-media companies for many years. CEO Sam Altman has already testified before Congress about the risks AI poses. He is sure to be back.

Altman has repeatedly proposed that the government take an equity stake in his company and his competitors. If the U.S. owns part of OpenAI but others don’t bite, it could mean some political favor for the company. But it would also make OpenAI subject to political control that could hurt its competitive position. Rather than suggesting a straight government stake, Anthropic recently proposed investment accounts for Americans most affected by AI job losses. The accounts would hold shares of AI companies.

Any form of public-sector ownership of the companies would be a minefield and is just one of many political risks they will have to contend with in the years ahead. But fundamental differences between their two business models mean that political questions could loom larger over OpenAI in the long run, even if Anthropic is under a brighter spotlight now.

The Global AI Race

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