This Is Why AI is a Bubble — and What EU Should Do

Federico Zebele

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This Is Why AI is a Bubble — and What EU Should Do<br>What the consensus says. What it stays silent about. And what would actually happen if it burst.

Federico Zebele<br>Jun 21, 2026

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Introduction

There is a precise moment when a bubble stops being an unpopular idea and becomes consensus. For AI, we are there.<br>Matt Stoller, one of the most widely read economic journalists in the United States, opened his latest piece with a clear observation: it is now consensus that we are in an AI investment bubble, and that this bubble represents a risk to the broader economy. It is no longer a contrarian position. It has become the starting point.<br>Thanks for reading! Subscribe for free to receive new posts and support my work.

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Stoller is not alone. Michael Burry — the hedge fund manager who predicted and bet against the 2008 subprime mortgage collapse, made famous by the film The Big Short — has opened a short position (a bet that prices will fall) on the semiconductor ETF SOXX, expiring January 2027. He has said publicly: “the market has overshot, the end is near.”<br>The problem is not that these voices do not exist. The problem is that the public debate keeps telling the same story. The spend-vs-revenue gap. The dot-com comparison. Valuations through the roof. All the right pieces, packaged in a way that makes them feel already processed, already priced in, already old news.<br>What follows is an attempt to go deeper. Not just what the articles say — but what they do not say, and why.

1. The Spend-vs-Revenue Gap: The Number Everyone Cites and Nobody Finishes Reading

The number you find in every article about AI is this: American companies are spending over $500 billion a year on AI infrastructure. Real consumer AI revenues sit at around $12 billion.<br>David Cahn, an analyst at Sequoia Capital — one of the most important venture capital funds in the world, the one that backed Apple and Google in their early days — calculated that the AI sector would need to generate roughly $600 billion in annual revenue just to cover the infrastructure it is building. That gap, which was $200 billion in 2023, grew to $600 billion in 2024. In 2026, with spending still accelerating, it is wider still.<br>But the number nobody actually finishes reading is the one belonging to OpenAI.<br>Text within this block will maintain its original spacing when publishedOn June 16, 2026, certified financial documents from OpenAI were obtained by journalist Ed Zitron and independently verified by the Financial Times. They were published days before OpenAI filed its confidential IPO prospectus with the SEC.<br>The numbers: in 2025, OpenAI reached $13.07 billion in revenue — more than triple the $3.7 billion of 2024. But total costs reached $34 billion, with $19.18 billion in research and development alone. Operating loss was $20.92 billion. Net loss reached $38.5 billion.

Leaked financial docs show OpenAI is losing billions of dollars a year — Source: ArsTechnica / Kyle Orland<br>To put this in perspective: for every dollar OpenAI earned, it spent $1.60. And that is already an improvement over 2024, when it spent $2.37 for every dollar it brought in.<br>Of those $34 billion in costs, $17.2 billion went directly to Microsoft for Azure cloud infrastructure and research compute. Microsoft, in return, paid OpenAI just $303 million. SoftBank paid $867 million. Come back to this when we reach the section on circular financing.<br>That math does not work even in an optimistic scenario. This is not a timing problem. It is structural.

2. The Dot-Com Comparison: The Story We Use to Avoid Thinking

The comparison with the internet bubble of 2000 is the most effective way to make people feel informed without actually understanding anything. Everyone uses it, in both directions.<br>Bulls (those who believe prices will keep rising) say: “this time is different, the companies have real revenues.” Bears (those who believe prices will fall) say: “it’s exactly like 1999.” Both are partially right, and that ambiguity is precisely the problem.<br>Let us start with what makes the current situation less severe than 2000:<br>The NASDAQ rose 125% from the launch of ChatGPT to its October 2025 peak. During the dot-com bubble, it rose 700%.

The forward P/E — the ratio between a stock’s price and its expected earnings over the next 12 months, a measure of how much the market is “paying” for future expectations — was at 79x at the dot-com peak. Today it sits around 25x.

Nasdaq 100 Index: current P/E Ratio - World PE Ratio<br>These numbers seem reassuring. But they obscure something important.<br>The total value of the US stock market today approaches $80 trillion. That is roughly twice what it was at the dot-com peak. It is 2.5 times the size of the entire American economy. Economist Dean Baker has calculated that a simple return to the long-run historical average would strip, on average, $300,000 in paper...