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On October 21, 2026, Gartner released a forecast stating that there is a gap of approximately $4.9 trillion between AI data center investment and revenue. Its calculations show that data center owners will need to generate a cumulative $8.5 trillion in revenue by 2030 to cover announced capital expenditures and financing costs and achieve a 12% return on investment; however, over the same period, enterprise and consumer AI revenue attributable to these data centers will not exceed $3.6 trillion. Gartner expects AI infrastructure spending to approach $1 trillion in 2026, with another $6 trillion invested from 2027 to 2030, and states that if the current pace continues, more than $3.5 trillion of AI infrastructure spending could face impairment by 2030. The firm also predicts that by 2030, cost pressures and the lack of differentiated business models will force more than 80% of neocloud providers to cease independent operations. There are currently no further developments.
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Gartner releases forecast of AI data center return-on-investment gap
Source:Fortune AI
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Oct 21
Fortune AI
Gartner says AI infrastructure will need $8.5 trillion in revenue by 2030, with a gap of nearly $4.9 trillion
Gartner estimates that data center owners will need to generate a cumulative $8.5 trillion in revenue by 2030 to cover announced capital expenditures and financing costs and achieve a 12% return on investment, but over the same period, enterprise and consumer AI revenue attributable to these data centers will not exceed $3.6 trillion, leaving a gap of about $4.9 trillion. Gartner expects AI infrastructure spending to approach $1 trillion in 2026, with another $6 trillion invested from 2027 to 2030. If the current pace continues, more than $3.5 trillion in AI infrastructure spending could face impairment by 2030. Gartner also predicts that by 2030, cost pressures and the lack of differentiated business models will force more than 80% of neocloud providers to cease independent operations.