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For almost as long as the artificial intelligence boom has been in full swing, there have been warnings of a speculative bubble that could rival the dot-com craze of the late 1990s that ended in a spectacular crash and a wave of bankruptcies.
Tech firms are spending hundreds of billions of dollars on advanced chips and data centers, not just to keep pace with a surge in the use of chatbots such as ChatGPT, Gemini and Claude, but to make sure they’re ready to handle a more fundamental and disruptive shift of economic activity from humans to machines. The final bill may run into the trillions. The financing is coming from venture capital, debt and, lately, some more unconventional arrangements that have raised eyebrows on Wall Street.
Even some of AI’s biggest cheerleaders acknowledge the market is frothy, while still professing their belief in the technology’s long-term potential. AI, they say, is poised to reshape multiple industries, cure diseases and generally accelerate human progress.
Yet never before has so much money been spent so rapidly on a technology that, for all its potential, remains somewhat unproven as a profit-making business model. Tech industry executives who privately doubt the most effusive assessments of AI’s revolutionary potential — or at least struggle to see how to monetize it — may feel they have little choice but to keep pace with their rivals’ investments or risk being out-scaled and sidelined in the future AI marketplace.
What are the warning signs for AI?
When Sam Altman, the chief executive of ChatGPT maker OpenAI, announced a $500-billion AI infrastructure plan known as Stargate alongside other executives at the White House in January, the price tag triggered some disbelief. Since then, other tech rivals have ramped up spending, including Meta’s Mark Zuckerberg, who has pledged to invest hundreds of billions in data centers. Not to be outdone, Altman has since said he expects OpenAI to spend “trillions” on AI infrastructure.
To finance those projects, OpenAI is entering into new territory. In September, chipmaker Nvidia Corp. announced an agreement to invest up to $100 billion in OpenAI’s data center buildout, a deal that some analysts say raises questions about whether the chipmaker is trying to prop up its customers so that they keep spending on its own products.
The concerns have followed Nvidia, to varying degrees, for much of the boom. The dominant maker of AI accelerator chips has backed dozens of companies in recent years, including AI model makers and cloud computing providers. Some of them then use that capital to buy Nvidia’s expensive semiconductors. The OpenAI deal was far larger in scale.
OpenAI has also indicated it could pursue debt financing, rather than leaning on partners such as Microsoft Corp. and Oracle Corp. The difference is that those companies have rock-solid, established businesses that have been profitable for many years. OpenAI expects to burn through $115 billion of cash through 2029, the Information has reported.
Other large tech companies are also relying increasingly on debt to support their unprecedented spending. Meta, for example, turned to lenders to secure $26 billion in financing for a planned data center complex in Louisiana that it says will eventually approach the size of Manhattan. JPMorgan Chase & Co. and Mitsubishi UFJ Financial Group are also leading a loan of more than $22 billion to support Vantage Data Centers’ plan to build a massive data-center campus, Bloomberg News has reported.
So how about the payback?
By 2030, AI companies will need $2 trillion in combined annual revenue to fund the computing power needed to meet projected demand, Bain & Co. said in a report released in September. Yet their revenue is likely to fall $800 billion short of that mark, Bain predicted.
“The numbers that are being thrown around are so extreme that it’s really, really hard to understand them,” said David Einhorn, a prominent hedge fund manager and founder of Greenlight Capital. “I’m sure it’s not zero, but there’s a reasonable chance that a tremendous amount of capital destruction is going to come through this cycle.”
In a sign of the times, there’s also a growing number of less proven firms trying to capitalize on the data center goldrush. Nebius, an Amsterdam-based cloud provider that split off from Russian internet giant Yandex in 2024, recently inked an infrastructure deal with Microsoft worth up to $19.4 billion. And Nscale, a little-known British data center company, is working with Nvidia, OpenAI and Microsoft on build-outs in Europe. Like some other AI infrastructure providers, Nscale previously focused on another frothy sector: cryptocurrency mining.
So is this 1999 all over again?
As with today’s AI boom, the companies at the center of the dot-com frenzy drew in vast amounts of investor capital, often using questionable metrics such as website traffic rather than their actual ability to turn a profit. There were many flawed business models and exaggerated revenue projections. Telecommunication companies raced to build fiber-optic networks only to find the demand wasn’t there to pay for them. When it all crashed in 2001, many companies were liquidated, others absorbed by healthier rivals at knocked-down prices.
Echoes of the dot-com era can be found in AI’s massive infrastructure build-out, sky-high valuations and showy displays of wealth. Venture capital investors have been courting AI startups with private jets, box seats and big checks. Many AI startups tout their recurring revenue as a key metric for growth, but there are doubts as to how sustainable or predictable those projections are, particularly for younger businesses. Some AI firms are completing multiple mammoth fundraisings in a single year. Not all will necessarily flourish.
“I think there’s a lot of parallels to the internet bubble,” said Bret Taylor, OpenAI’s chairman and the CEO of Sierra, an AI startup valued at $10 billion. Like the dot-com era, a number of high-flying companies will almost certainly go bust. But in Taylor’s telling, there will also be large businesses that emerge and thrive over the long term, just as happened with Amazon.com Inc. and Alphabet Inc.’s Google in the late ’90s.
“It is both true that AI will transform the economy, and I think it will, like the internet, create huge amounts of economic value in the future,” Taylor said. “I think we’re also in a bubble, and a lot of people will lose a lot of money.”
Amazon Chairman Jeff Bezos said the spending on AI resembles an “industrial bubble” akin to the biotech bubble of the 1990s, but he still expects it to improve the productivity of “every company in the world.”
There are also some key differences to the dot-com boom that market watchers point out, the first being the broad health and stability of the biggest businesses that are at the forefront of the trend. Most of the “Magnificent Seven” group of U.S. tech companies are long-established giants that make up much of the earnings growth in the Standard & Poor’s 500 Index. These firms have huge revenue streams and are sitting on large stockpiles of cash.
Despite the skepticism, AI adoption has also proceeded at a rapid clip. OpenAI’s ChatGPT has about 700 million weekly users, making it one of the fastest-growing consumer products in history. Top AI developers, including OpenAI and Anthropic, have also seen remarkably strong sales growth. OpenAI previously forecast revenue would more than triple in 2025 to $12.7 billion. While the company does not expect to be cash-flow positive until near the end of this decade, a recent deal to help employees sell shares gave it an implied valuation of $500 billion — making it the world’s most valuable company never to have turned a profit.
Fiegerman and Reinicke write for Bloomberg.
