The AI Demand Bubble
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The AI Demand Bubble
Ed Zitron<br>Aug 4, 2026<br>31 min read
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If you liked this piece, you should subscribe to my premium newsletter. It’s $70 a year, or $7 a month, and in return you get a weekly newsletter that’s usually anywhere from 5,000 to 18,000 words, including vast, detailed analyses of NVIDIA, Anthropic and OpenAI’s finances, and the AI bubble writ large. My Hater's Guides To the SaaSpocalypse, Private Credit and Private Equity are essential to understanding our current financial system, and my guide to how OpenAI Kills Oracle pairs nicely with my Hater's Guide To Oracle, as well as the Hater’s Guide To Oracle (Part 2).<br>Subscribing to premium is both great value and makes it possible to write these large, deeply-researched free pieces every week. On Friday, I’ll publish the second installment of the Hater’s Guide to Nvidia — where I’ll take a look at how the AI bubble transformed the company from a pure hardware player to a purveyor of the financial dark arts.<br>If you want to get in touch — and especially if you have any juicy information about Anthropic, OpenAI, or any other companies in the AI bubble — hit me up on Signal at ezitron.76. I’m also on IB on The Terminal.<br>Soundtrack: Tool - Forty Six & 2<br>The question I want to ask anyone reading this who might have invested in or in some way backed the hyperscalers and the greater AI industry:<br>What is it you think you’ve gotten yourself into? Because I think you’re being sold a lie.<br>Last week’s tech earnings saw outlet after outlet claim that Amazon, Google, and Microsoft’s AI bets were “paying off” as their respective cloud segments reported record revenue growth, casually ignoring that none of them have broken out their AI revenues. To add insult to injury, Microsoft decided, after sharing that it had a $37 billion AI run rate (about $3.08 billion a month) in Q3 FY2026, that it simply didn’t have to share anything about its actual AI payoff in Q4, realizing that its overall numbers would beguile reporters and analysts — especially those with little interest in what was actually going on as long as the topline stuff looked good.<br>To be clear, all three of these companies’ cloud platforms have many other customers paying for many other things other than generative AI services or AI GPUs, and they’ve all engaged in a combination of multiple outright price increases and changing their core subscriptions to force AI features on them as a means of boosting revenues and conning the street into believing that “AI is paying off” every time they non-consensually thrust it on their customers, framing higher prices as “better value” in a way that fucks the user to appease Wall Street.<br>Yet the biggest con of all is that a vast majority of this revenue growth comes from the compute spend of Anthropic and OpenAI, both of whom account for the vast majority of AI revenues and overall cloud growth we’ve seen in the last few years.<br>Every publication you read right now will tell you that AWS and Azure and Google Cloud are growing like wildfire as a result of the hundreds of billions of dollars they’ve invested in AI GPUs and data centers, when the truth is far simpler: their revenues are being buoyed by two unprofitable, unsustainable AI labs that cannot exist without being funneled tens of billions of dollars each year.<br>And a decent chunk of that money is coming from the hyperscalers themselves. In the last seven months alone, Google has sunk $10 billion (and up to $30 billion more) into Anthropic, with Amazon funnelling $5 billion to Anthropic within a week of that investment and a total of $50 billion into OpenAI. For all the concern about circular financing in the AI world, it’s astonishing that so much attention has (rightly, to be clear) centered on NVIDIA’s backstopping and funding of neoclouds, and less on the fact that hyperscalers are propping up their now biggest customers, giving them cash that will eventually migrate back to the hyperscaler.<br>I’d also argue that the vast majority of their capex exists to support these two load-bearing failsons. A few months ago, a Microsoft executive told the judge during the Musk-Altman trial that its OpenAI relationship had cost it “over $100 billion,” including both the $13 billion it sunk into the company and the associated infrastructure.<br>Microsoft has dedicated its Fairwater data centers (however much actually exists) entirely to OpenAI, much like Amazon has for Anthropic with however much of its massive Indiana-based Project Rainier has actually been turned on, and much like Google is in talks to backstop a $15 billion data center project for Anthropic, along with data centers with Cipher Mining and TeraWulf and a $35 billion private credit-funded Broadcom-backstopped deal where Google will sell Anthropic its TPU AI chips, put them in a Google-built data center, and rent them back to Anthropic.<br>I want to spell this out: when...