Gartner Forecasts Over $3.5 Trillion in AI Infrastructure Investment at Risk of Impairment by 2030

Research advisory firm Gartner released a forecast on October 14, 2026, indicating that the artificial intelligence industry faces significant pressure to recoup investments. Using a 12% return on invested capital (ROIC) as the threshold for viable investment, Gartner estimates that AI data center operators need to generate a cumulative $8.5 trillion in revenue by 2030 to cover announced capital expenditures and financing costs while achieving this return. However, enterprise and consumer AI revenue attributable to AI data centers during the same period is projected to be at most $3.6 trillion, leaving a gap of $4.9 trillion.

Will Sommer, Senior Director Analyst at Gartner, stated that AI companies are expected to invest nearly $1 trillion in building AI infrastructure in 2026, with an additional $6 trillion planned between 2027 and 2030. Because most AI-native companies operate with asset-light models, firms owning large amounts of AI infrastructure will capture less than half of the AI revenue. According to the analysis, total revenue from AI software, services, and consumer products is estimated at only $4.4 trillion by 2030, with at most 30% available to recover underlying capital investments.

Gartner warns that if AI companies maintain their current pace of capital expenditure, more than $3.5 trillion in AI infrastructure spending could face asset impairment risk by the end of 2030; if investment continues along its current trajectory, assets facing write-down risks could exceed $4 trillion by 2032. Additionally, Gartner predicts that cost pressures and undifferentiated business models will force over 80% of Neoclouds (new cloud service providers centered on AI computing) to cease independent operations by 2030, leading to market consolidation before that year.