Monologue: The AI Data Center Overbuild
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Hello and welcome to this week's Better Offline monologue. I'm your host at Zitron.
Better all fine.
As ever, subscribe to the newsletter, premium, you know all that good stuff, I'll have the links in there. And this week I want to talk about actually a free newsletter I put out called Where Are All the AI chips? And it turns out that the answer is either in warehouses or unpowered data centers. In an investigation with The Guardian, Aisha Down over there worked on it with me, she's awesome, I reported that Microsoft only had 2.2 million GPUs in servers, far less than people believed. And while I couldn't report it at the time because I still had to run down some leads, the total power of the chips was estimated at about 1.993 gigawatts of capacity, with the overall cost of those GPUs installed somewhere in the region of $50 to $60 billion.
A few weeks ago, Bloomberg reported that despite reporting that Microsoft had added a gigawatt in each of the last three quarters, and by reporting I mean the things that Microsoft literally said on their earnings call, that only two gigawatts out of their total twelve gigawatts of data center capacity was specifically for AI. In other words, despite having spent over $265 billion on capital expenditures since the beginning of 2022, Microsoft has only put about $50 billion worth of GPUs into service. And I estimate that as much as $106 billion worth of GPUs and associated hardware are now sitting either unpowered in data centers, or incomplete data centers, or in warehouses, and that very little AI computers coming online through the data.
throughout the entire industry. Microsoft's CEO Satchin Adela had sort of admitted this in November of last year, when he told an interviewer that he had a bunch of chips sitting in inventory that he couldn't plug in and that's a quote, though he didn't mention the sheer scale of the warehousing or indeed how little he'd actually turned on. Well, I'm a curious little critter, so I went looking for more evidence of the problem outside of Microsoft, and found it buried in the balance sheets of multiple hyperscalers and neo clouds under the construction in progress line on the balance sheet, which is specifically where companies bury their uninstalled GPUs and incomplete data centers. And this number has grown across a ton of them, well, by a remarkable amount.
Google, Meta, Oracle, Amazon, SpaceX, and Tesla, neo clouds like CoreWave and Iron, and co-location companies like Core Scientific and Applied Digital all have about $374 billion of construction in progress. A figure that's likely lower than the true number, because Amazon's contribution, which is about $71 billion, is only current as of the end of 2025. And there have been two, now th very soon, three more quarters. quarters of that. And the company only reports annual, like I said. A large chunk of that larger CIP number is Google's, which sits around $122 billion, which is truly shocking. And in every case, by the way, the number has grown every single time it's been reported for the last twelve quarters.
Is it with some fluctuation in the case of Amazon because of their logistics operations, but really right now it's only growing. Now, not everybody reports construction in progress, so that number doesn't include Microsoft, Firma, Sharon, Equinex, Nebius, Poolside, private operators like Vantage, any of the sovereign AI build-outs in the Middle East or Europe, the private projects built for OpenAI and Anthropic, or any of Oracle or Meta's off-balance sheet construction projects, which were likely, I think, numbering in tens of billions of dollars.
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Chapters
4 chapters
1
What is the main topic discussed in this episode?
0:00–4:15
2
What is the core issue of AI GPU overcapacity that Ed Zitron introduces?
4:15–6:31
3
How did the investigation reveal Microsoft’s actual GPU inventory and power capacity?
6:31–11:08
4
Why are hyperscalers’ reported AI gigawatt figures considered misleading?
11:08–11:51