Gartner Says Over $3.5 Trillion of AI Infrastructure Spending Could Be Exposed to Impairment by the End of 2030.
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.
“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.
By 2030, Gartner predicts that cost pressure and a lack of a differentiating business model will force over 80% of neocloud providers to cease independent operations.
Gartner estimates AI-optimized IaaS spending will grow from $66 billion in 2027 to $174 billion in 2030. “The growth in spending on AI-optimized IaaS will be too low for most AI compute providers to recover their AI investments before the current generation of AI semiconductors is replaced,” said Sommer.
By 2030, Gartner predicts that cost pressure and a lack of a differentiating business model will force over 80% of neocloud providers to cease independent operations.
