The AI ​​industry runs on FOMO

For big tech companies, a penny invested in AI is a penny earned… maybe. After an indefinite period of time. Investors hope.

On earnings calls last week, Amazon, Google, Microsoft, and Meta announced spending more than $350 billion this year on capital expenditures., Or long-term investments in the future of the company. All four told investors to expect the number to rise even more next year: Microsoft said “higher,” Amazon said “increased,” Google said “significantly larger,” and Meta said “significantly larger.”

This will likely translate into more than $400 billion total for the four companies next year, according to Joe Vath, partner and head of growth at Eclipse VC.

The return on investments for these companies so far is unclear. Meanwhile, custom AI companies are burning through cash: OpenAI has reportedly taken a hit 12 billion dollars in annual revenue this summer – while it is said to be on track for success 115 billion dollars Until 2029.

Fatah said that tension over this mismatch is escalating. He added that there is “a push and pull between these companies and investors.” “Investors are saying: Am I going to get a return on this spending?” It’s one of the increasingly clear indicators that some parts of the AI ​​industry are a bubble — but it doesn’t yet tell us what happens after it bursts.

The hype around AI has been very high for several years, and startup valuations have reached staggering numbers. OpenAI, for example, is It is said It hopes for a $1 trillion IPO in 2026 or 2027 and plans to raise $60 billion or more.

But AI companies insist there is not enough money to buy chips, data centers and other resources. In a Q&A with reporters at OpenAI’s annual DevDay event last month, the executives spoke out He stressed repeatedly They worried about the lack of computing to expand services like Sora’s video generation AI and ChatGPT’s daily pulse feature, and discussed the need to eventually monetize these services. Amazon, Google and Microsoft — which offer cloud services on a rapidly growing scale — “have all indicated that they are very limited in their capacity,” said Molly Alter, a partner at Northzone VC. Edge.

If these claims are accurate, they suggest that simply coming up with good products won’t be enough to make AI companies profitable — because they can’t afford to scale those products to support a huge user base. Even if they are overpriced, the systems are very expensive to operate. OpenAI is still believed to be so Losing money Even at the $200 monthly subscription level for ChatGPT, thanks to the cost of running queries.

Alter added that OpenAI’s IPO is a perfect example of the puzzle. The company wants to secure about 26 gigawatts of computing capacity for data centers (which translates to about $1.5 trillion at current costs per Alter) — which means that even with the company’s current revenues, up to $100 billion in investment from Nvidia, and other “circular deals,” Alter says it still can’t understand how to solve the company’s glaring financing gap.

Some of the company’s investors are asking the same questions. OpenAI investor Brad Gerstner and CEO of Altimeter Capital asked Sam Altman, CEO of OpenAI. Podcast on Friday about how a company with $13 billion in revenue can make $1.4 trillion in spending commitments.

“First of all, we’re generating more revenue than that; second, Brad, if you want to sell your shares, I’ll find you a buyer,” Altman replied. “I just…enough.”

In past quarters, executives at big tech companies have presented customizable models and AI agents as a saving grace that would surely eventually turn a profit — emphasizing that they need to… Spend money to make moneyIncluding by cutting costs elsewhere and shifting resources to artificial intelligence.

Now, agents from OpenAI, Google, and others are in the hands of users. Despite companies’ promises that they will steadily improve in automation,arduous tasks,“In their current state, they are not conquering the world.

Investors seemed interested in the details of Meta’s expected expansion, and their demands for details were not always met with clear answers. “There are a lot of moving parts in the budget. It’s not finalized yet. It’s still being put together,” CFO Susan Lee responded to a question. “We don’t have, you know, specific goals to share.”

Some investors seemed cautious about whether there was a coherent plan at all. Meta made headlines in 2025 for spending billions to lure AI engineers and researchers away from competitors to its brand-new Superintelligence team, then announced internal restructuring and layoffs soon after. The Meta’s AI initiative comes on the heels of a fictional endeavor for the virtual reality world “Metaverse,” in which it still exists today. spent and lost Tens of billions through its Reality Labs division. “I don’t think they’re getting any results that would lead you to think this is good spending,” Fatah said. Edgetalks about reality laboratories.

Some of the same concerns were present on other companies’ earnings calls, where investors asked about the AI ​​industry’s hype levels, capacity limitations, and feature adoption. On Microsoft’s earnings call, one investor asked: “Honestly, are we in a bubble?”

Even technology executives have admitted that some aspects of the industry may be overblown. OpenAI’s Altman told reporters last month that there are “a lot of parts of AI that I think are kind of a bubble right now.” On Microsoft’s most recent earnings call, CEO Satya Nadella told investors: “I don’t believe that AGI as defined, at least by us in our contract, will be achieved anytime soon.” But bubbles are largely driven by sentiment and behavior, as well as fear of missing out and expertly marketing corporate narratives.

If it is a bubble, the consensus seems to be that it will not cause the industry to explode; It will only lead to fewer players and more consolidation. Alter said the funding gaps within the industry keep her awake, especially since a company’s investment in its future growth should ideally lead to real growth and ultimately profits. The companies that succeed may not be the most attractive or the most consumer-oriented – think programming agents, AI for customer service, and perhaps creative content generation, rather than just AI-powered social media and general-purpose chatbots.

But there’s no fighting AI FOMO, so any bubbling parts of the industry have no sign of slowing down yet — but Fath said he’s keeping an eye on whether OpenAI slows down for any reason, and the same goes for Nvidia’s data center business.

“I think when the board meets there, they ask the CEO: ‘What are you doing about AI?’” Fath said. “That’s the question they’re asking. They have to come up with a ready-made answer to say how they’re going to spend on that. And if the business starts to go down, and they don’t spend on AI, there’s going to be a lot of criticism of those CEOs… even if we don’t really know what the returns are going to look like right now.”

“This gets into the ‘FOMO’ that is built across industries and across companies to make sure you’re not on the wrong side of change.”

And if overinvestment in AI becomes the wrong side of change? Well, at least everyone was doing that.