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\t\t\tIllustration by Tag Hartman-Simkins \/ Futurism. Source: Getty Images<\/p>\n
In August, the founder of hedge fund Praetorian Capital Harris \u201cKuppy\u201d Kupperman penned an essay<\/a> on the absurd finances behind AI data centers. While the tech industry has likened data centers<\/a> \u2014 or more specifically, the expensive semiconductor chips that power them \u2014 as the \u201cshovels\u201d of the AI gold rush, Kupperman\u2019s napkin math found that AI data centers have an impossibly short runway<\/a> to achieve profitability.<\/p>\n In short, this is because data center components age rapidly<\/a>, either made obsolete through rapid advances in technology, or broken down over years of constant, high-powered usage.<\/p>\n After publishing his initial findings, Morningstar reports<\/a> that Kupperman got an earful from anxious professionals in the data center industry. Thanks to those conversations, the investment manager realized he made a crucial mistake \u2014 and that because of it, his grim prediction may not have been cynical enough.<\/p>\n \u201cI clearly hit a nerve in the industry, when judging by the number of individuals who reached out to chat,\u201d he wrote in an followup blog post<\/a>. \u201cIn total, I\u2019ve spoken with over two-dozen rather senior people in the datacenter universe, and there was an interesting and overriding theme to our conversations; no one understands how the financial math is supposed to work. They are as baffled as I am, and they do this for a living.\u201d<\/p>\n Kupperman\u2019s original skepticism was built on a guess that the components in an average AI data center would take ten years to depreciate, requiring costly replacements. That was bad enough: \u201cI don\u2019t see how there can ever be any return on investment given the current math,\u201d he wrote at the time.<\/p>\n But ten years, he now understands, is way too generous. <\/p>\n \u201cI had previously assumed a 10-year depreciation curve, which I now recognize as quite unrealistic based upon the speed with which AI datacenter technology is advancing,\u201d Kupperman wrote. \u201cBased on my conversations over the past month, the physical data centers last for three to ten years, at most.\u201d<\/p>\n In his previous analysis, Kupperman assumed it would take the tech industry $160 billion of revenue to break even on data center spending in 2025 alone. And that\u2019s assuming an incredibly generous 25 percent gross margin<\/a> \u2014 not to mention the fact that the industry\u2019s actual AI revenue is closer to $20 billion annually, as the investment manager noted in his previous blog.<\/p>\n \u201cIn reality, the industry probably needs a revenue range that is closer to the $320 billion to $480 billion range, just to break even on the capex to be spent this year,\u201d Kupperman posited in his updated essay. \u201cNo wonder my new contacts in the industry shoulder a heavy burden \u2014 heavier than I could ever imagine. They know the truth.\u201d<\/p>\n Kupperman called that gulf between tech industry spending and actual revenue in 2025 \u201castonishing.\u201d However, it doesn\u2019t even begin to scratch the surface. For example, how does it all shake out when we account for 2026, when hundreds of new data centers are expected to pop up?<\/p>\n \u201cAdding the two years together, and using the math from my prior post, you\u2019d need approximately $1 trillion in revenue to hit break even, and many trillions more to earn an acceptable return on this spend,\u201d he writes.<\/p>\n \u201cIf the economics don\u2019t work, doing it at massive scale doesn\u2019t make the economics work any better \u2014 it just takes an industry crisis and makes it into a national economic crisis,\u201d he concludes.<\/p>\n Overall, the pessimists broadly agree: it\u2019s no longer a matter of if AI is massively overhyped, but when the whole thing comes crashing down.<\/p>\n