翻訳待ち：The AI Demand Bubble

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。

The AI Demand Bubble Ed Zitron Aug 4, 2026 31 min read 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). 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. 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. Soundtrack: Tool - Forty Six & 2 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: What is it you think you’ve gotten yourself into? Because I think you’re being sold a lie. 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. 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. 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. 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. 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. 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. 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. I want to spell this out: when you remove Anthropic and OpenAI’s compute spend, I am not confident that Google, Microsoft and Amazon have much of an AI business. While many people believe — largely because the big three refuse to break out their actual AI revenues or disclose their customer concentration — that they have AI revenues coming from a diverse set of different customers, the reality is that their largest cloud customers, let alone AI customers, are two companies that can literally not afford to pay them without a near-infinite flow of venture capital or debt. Analysts Estimate That More Than 70% of Amazon, Microsoft and Google’s AI Revenues Come From OpenAI and Anthropic Per Ross Sandler of Barclays, Anthropic and OpenAI are estimated to make up 73% of all of Amazon’s AI revenues in both 2026 and 2027 and 75% of AI revenues in 2028, with Anthropic spending $14.1 billion in 2026, $25.3 billion in 2027, and $35.8 billion in 2028, and OpenAI spending $9 billion in 2026, $15 billion in 2027, and $20 billion in 2028. Amazon plans to spend $220 billion in capital expenditures in 2026 and even more in 2027, and appears to be doing so almost-exclusively to provide compute for a company that had to raise $95 billion in funding in the space of six months, with $5 billion of that coming from Amazon itself. Editor’s Note: Just before I headed to press on this piece, I found another note from Stephen Ju (who you’re just about to learn about for the first time) about AWS revenues, with the numbers a little different. He has estimated total AI revenues at around $30.9 billion for 2026, with OpenAI and Anthropic’s compute spend sitting at 59% of those revenues ($18.3 billion) and the remaining $12.6 billion coming from Bedrock, the platform from which Amazon sells access to both TPUs and AI models from Anthropic and (more recently) OpenAI. This revenue concentration improves to 55% in the 2027 estimates. Anyway, the rest of this piece focuses on Sandler’s numbers, as I did not get a ton of time to dig over these. These numbers, while different, do not meaningfully change my perspective. As I’ll argue about Vertex, making money by proxy of having monopoly permission to sell OpenAI and Anthropic’s models absolutely counts as revenue related to Anthropic and OpenAI to me. A chunk of both labs’ revenue comes from the resale of these models, easy money that also becomes another way in which hyperscalers feed their revenues back into the AI labs so that the AI labs can spend the money on compute. I will add that Microsoft no longer pays a revenue share to OpenAI. In any case, the viability, efficacy, and attractiveness of these models are still a product of Anthropic and OpenAI’s ongoing work. Google is in a similar-position. Per Stephen Ju of UBS, “...Anthropic, OpenAI and Meta will account for 21%, 7% and 1% of 2026 Google Cloud revenues, respectively, and 44%, 5% and 1% of 2027 revenues,” or, put another way, 28% of all 2026 and more than 48% of all 2027 Google Cloud revenues are from Anthropic and OpenAI. Ju also estimates Meta will make up a whopping 1% of Google Cloud revenues in each year, and does not mention a single other customer, which heavily-suggests that there aren’t really any large ones. Based on Bloomberg Intelligence’s consensus estimates for Google Cloud’s revenues in 2026 ($105.9) and 2027 ($173.8), OpenAI and Anthropic represent $29.4 billion ($7.4bn/$22bn) in 2026 and $84.69 billion ($8.69bn/$76bn) in 2027. To be explicit here, this is all Google Cloud revenues. It is reasonable to believe that this represents at least 75% of Google’s AI revenue, if not more. What’s crazy is that these numbers are actually lower than UBS’ estimates. As the chart below demonstrates, OpenAI and Anthropic’s spend is estimated to sit at over $35 billion in 2026, larger than both its entire Google Cloud core non-AI business and Vertex AI model rental business that is largely boosted by Google’s ability to sell Anthropic’s models. Sidenote: Ju and Sandler appear to disagree on how much of Anthropic’s compute spend that Amazon and Google get, which is fair, because both Google and Amazon separately claim to be Anthropic’s primary provider. Eagle-eyed readers will also see that Google’s non-AI cloud business is estimated to be effectively flat in 2026, 2027, and 2028. I also don’t think it’s common knowledge that OpenAI is such a large customer of either Google Cloud or Amazon Web Services, spending at least an estimated $52.5 billion in 2026 and at least an estimated $125 billion in 2027. In the Musk-Altman trial, OpenAI estimated it would spend $50 billion on compute in 2026, and based on those estimates, that gives us about $16.4 billion across Amazon and Google, leaving a likely $33.6 billion in spend left for Microsoft Azure, though I’ll add that OpenAI continually underestimates its own compute spend and losses. And based on a note from Michael Turrin of Wells Fargo from May 31 2026, things are just as bad for Microsoft, with 70% or more of its AI revenues coming from Anthropic and OpenAI. While Turrin “expects investments at software & models layers [to] pay off in meaningful adoption over time,” it’s difficult to argue that Microsoft has any meaningful AI strategy outside of OpenAI and Anthropic’s compute spend. To make matters worse, based on Wells Fargo’s estimates, it appears that Microsoft 365’s AI revenues are barely — and I mean barely — beating the revenue share Microsoft gets from OpenAI’s sales. Wells Fargo also includes a helpful cheat sheet of its estimates for AI contributions, estimating that even at the very end of FY2027 (which began on July 1 2026), OpenAI and Anthropic’s spend will represent a dramatic 74% of all AI revenues. Wells Fargo also estimates that the two AI labs represented 23% of Azure revenue in FY2026, growing to 35% in FY27. Considering Azure grew 41% year-over-year, this means that 40% or more of Microsoft Azure’s growth came from them — and remember, Azure sells far more than just AI services. This is an absolute fucking scandal. The vast majority of Microsoft, Google and Amazon’s AI revenues and revenue growth in their representative cloud platforms are from Anthropic and OpenAI, and they are blatantly, unashamedly misleading investors by not disclosing that this is the case. We’re talking 73% of AWS’ AI revenues, 74% of Microsoft’s, and likely 70%+ of Google Cloud’s considering that just Anthropic and OpenAI’s AI spend is expected to be more than 48% of all cloud revenues. This is not me being a hater, a skeptic, or a doomer, but the product of actually investigating what’s happening in the real world rather than just looking at whatever numbers the hyperscalers fart out and assuming it’s “all from AI,” and that “AI” means something more than just the two main model labs. Investors in Amazon, Google and Microsoft have been led to believe that the $994 billion spent on AI GPUs and data centers exists to boost their existing businesses and build what amounts to the next industrial revolution. In f [truncated for AI cost control]