Gartner forecasts $4.9 trillion gap in AI investment returns by 2030 — Fortune
Research firm Gartner forecasts that data center owners will need to generate a combined $8.5 trillion in revenue by the end of 2030 to justify planned investments in artificial intelligence infrastructure. At the same time, no more than $3.6 trillion from corporate and consumer AI revenues may reach these data centers, according to the company’s estimate. Thus, the gap will amount to $4.9 trillion, Fortune reports.
Spending outpaces revenue
According to Gartner’s calculations, global capital expenditure on AI in 2025–2030 will reach $7.5 trillion. In 2026, AI providers are expected to spend nearly $1 trillion on relevant infrastructure, and another $6 trillion in 2027–2030. Annual capital expenditure of this kind could approach $2 trillion by 2030, accounting for more than 1% of global GDP.
Gartner estimates total revenue from AI-based software, services and consumer products at $4.4 trillion by 2030. At the same time, only up to 30% of this amount, according to the company’s estimate, will be allocated to cover core capital investments in data centers and computing chips. The remaining revenue will go to companies selling applications, models and other services built on this infrastructure.
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Risk of asset write-downs
Gartner warns that if current spending rates persist, more than $3.5 trillion in AI infrastructure investments could be at risk of impairment and write-downs by the end of 2030. By 2032, this risk could exceed $4 trillion. The estimate of the need for $8.5 trillion takes into account announced capital expenditure, financing costs and a target return on invested capital of 12%. The company does not expect this level to be reached before the end of 2032.
In Gartner’s view, major cloud companies, including Amazon, Microsoft and Alphabet, have diversified businesses and existing cash flows that can support their investments. Smaller specialized cloud providers, or neoclouds, are more vulnerable: the company forecasts that by 2030, more than 80% of such providers will cease operating independently due to cost pressure and the lack of a distinctive business model.
