Ed Zitron Just Disproved the Core Claim Behind His AI Bubble Case
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Ed Zitron Just Disproved the Core Claim Behind His AI Bubble Case<br>OpenAI financial data leaked to the industry’s biggest hater settles an open question — just not in his favor
Garrison Lovely<br>Jun 17, 2026
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Note to readers
I spent months digging into the case for and against the AI bubble for my forthcoming book Obsolete: The AI Industry’s Trillion-Dollar Race to Replace Us—and How to Stop It (Nation Books, preorders ship in August, wide release is September 15).<br>Preorder<br>Today’s piece focuses on the most common mistake in the bubble case, which we just got some welcome clarity on.
AI’s most dedicated hater, Ed Zitron, recently intoned that something big was coming:<br>One of my sources has come forward and brought me a story that will possibly burst the AI bubble …<br>If you’re wondering what the story is, know that it’s the information I’ve wanted for years, delivered as I have always wanted it, and I will treat it with the reverence it deserves. Imagine what the worst possible thing for me to get would be and you’re probably close. …<br>I can guarantee you it’ll be worth it, and you’ll be stunned by what I report.
On Monday, Zitron came through, sharing OpenAI financial data that was leaked to him. He regularly publishes 15,000 word posts, but this time he kept it short and sweet, explaining that “Due to the seriousness of this story, I am not going to do very much editorializing, as the numbers speak for themselves.” While OpenAI’s losses are, as we’ll soon see, significant, the uncharacteristic lack of analysis may better reflect the fact that the numbers don’t actually comport with the story Zitron has been selling.<br>The blogger and public relations consultant has emerged as the loudest and brashest proponent of the idea that generative AI is a bubble, destined to pop… any day now. Zitron makes a lot of arguments to support his position. But the most load-bearing one of all is this: the generative AI companies driving the entire industry are losing money, even on their paying customers. Here’s him writing in September:<br>Generative AI companies — OpenAI and Anthropic included — lose millions or billions of dollars, and so do the companies building on top of them, in part because the costs associated with delivering models continue to increase. Integrating Large Language Models into your product already loses you money, at a price where the Large Language Model provider (EG: OpenAI and Anthropic) is losing money.<br>I believe that generative AI is, at its core, unprofitable, and that no company building their core services on top of models from Anthropic or OpenAI has a path to profitability outside of massive, unrealistic price increases.<br>The only realistic path forward for generative AI firms is to start charging their users the direct costs for running their services, and I do not believe users will be enthusiastic to do so, because the amount of compute that the average user costs vastly exceeds the amount of money that the company generates from a user each month (emphasis mine).
And here’s him on a podcast in November talking about OpenAI specifically:<br>We’re talking a company that just the cost of doing business is two or three times what they are making in revenue. And that’s just the inference. That’s before training.
Indeed, these companies are famously unprofitable (well, before Anthropic’s unprecedented revenue tear in recent months), so why does it matter so much how they’re losing money? Well, if each additional paying customer costs more to serve than they pay you, then faster growth just brings you to bankruptcy faster. But if you profit from each new paying customer, then enough growth will bring you to overall profitability, even if you have high fixed costs (in this case, mostly from training future generations of AI models).
Put simply, if AI companies need to grow like crazy and fix their cost structure to ever become profitable, then yes, this does all look like a bubble. But if instead they profit from each unit sold, then they just need to grow like crazy to recoup training costs.<br>Public reporting and independent estimates have indicated that companies like OpenAI and Anthropic are profitable on serving their models, with healthy gross margins in the 30-60 percent range.
But these companies are still private, so we can’t inspect their books directly. Fortunately, someone leaked OpenAI’s audited financial statements to Zitron, who shared them with the Financial Times to validate their authenticity.<br>And wouldn’t you know it, OpenAI’s gross margins are positive and improving. In 2024, OpenAI’s cost of serving customers was $2.65 billion and its revenue was $3.7 billion (28 percent gross margins). Last year, cost of revenue reached $7.5 billion, but revenue more than tripled to reach $13.07 billion (43 percent gross margins).<br>Of course, this misses most of the costs OpenAI bore, which...