The AI capex cycle: doom, discipline, or differentiation?

A recent piece written by the Chief Investment Officer of an investment fund called Praetorian Capital, made waves with a stark claim: “Simple math says the AI investment boom is doomed.” His argument is clean: with $400B in data center capex forecast for 2025, and only ~$15-20B in visible AI revenues today, the economics can never work. The industry is destined to follow the well-worn path of fiber, shale, or shipping: glorious capacity buildouts followed by equity destruction. This kind of warning should not be dismissed lightly. Coming from a CIO, it reflects real capital-cycle intuition. And he’s right on the essentials: AI infrastructure buildouts are enormously capital-intensive, they refresh far faster than traditional infra, and they carry the same risk of stranded assets and overcapacity that have wrecked past booms. If you are a cautious allocator, you should be worried about the mismatch between depreciation clocks and revenue visibility. But the leap from this is risky to t

A recent piece written by the Chief Investment Officer of an investment fund called Praetorian Capital, made waves with a stark claim: “Simple math says the AI investment boom is doomed.” His argument is clean: with $400B in data center capex forecast for 2025, and only ~$15-20B in visible AI revenues today, the economics can never work. The industry is destined to follow the well-worn path of fiber, shale, or shipping: glorious capacity buildouts followed by equity destruction. This kind of warning should not be dismissed lightly. Coming from a CIO, it reflects real capital-cycle intuition. A