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Gartner says AI infrastructure spending could face $3.5 trillion in write-downs by 2030

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Gartner forecasts nearly $1 trillion in AI infrastructure spending in 2026 and another $6 trillion from 2027 to 2030. It says more than $3.5 trillion of that spending could need write-downs by the end of 2030 because revenue will not cover costs. Neoclouds are the most exposed, since their market grows too slowly to help them recoup investments before current AI chips are replaced.

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Gartner forecasts that AI providers will spend nearly $1T on infrastructure in 2026 and another $6T from 2027 to 2030, and says more than $3.5T of that spending could need write-downs by the end of 2030 because revenue won’t cover its cost

Much of that revenue also flows elsewhere, because most AI-native providers run asset-light models, so less than half of AI revenue will reach companies that own significant infrastructure.

Neoclouds, the GPU rental specialists below the hyperscalers, sit most exposed because they lack the diversified revenue that could let hyperscalers fund AI investment for years.

Their market grows too slowly to help, since AI-optimized IaaS spending rises from $66 billion in 2027 to $174 billion in 2030, which Gartner says won’t let most providers recoup investments before current AI chips are replaced.

Source: Rohan Paul · x.comPublished