More than $3.5 trillion of AI infrastructure spending could be exposed to impairment by the end of 2030, if AI providers continue their current pace of capital spending, according to Gartner, Inc., a business and technology insights company.

“In 2026, AI providers are expected to spend nearly $1 trillion on AI infrastructure, and are forecast to invest an additional $6 trillion between 2027 and 2030,” said Will Sommer, Sr Director Analyst at Gartner. “However, our research indicates that enterprise and consumer AI revenue will be insufficient to support profitable returns on all planned AI capital expenditures during this period.”

“Through 2030, AI data center owners would need to generate a cumulative $8.5 trillion in revenue to cover announced capital spending, financing costs, and a 12% return on invested capital (ROIC), which we assume to be the hurdle rate of investment capital,” said Sommer. “However, total enterprise and consumer AI revenue that can be attributed to AI data centers during this period is forecast to reach no more than $3.6 trillion. Because most AI-native providers operate asset-light business models, we predict that less than half of AI revenue will be earned by providers that own significant AI infrastructure.”

Failure to achieve sustainable ROIC on rapidly depreciating assets would almost certainly necessitate write-downs. Based on Gartner projections, a continued AI infrastructure investment trajectory could leave more than $4 trillion in asset value exposed to write-down risk through 2032. In this scenario, Gartner does not expect the 12% ROIC to be achieved until the end of 2032 at earliest....

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