The research firm projects a widening gap between AI infrastructure investment and revenue, with more than 80% of neocloud providers potentially losing their independent status by 2030.
More than $3.5 trillion in artificial intelligence infrastructure spending could face impairment risks by the end of 2030 if technology companies maintain their current investment trajectory, according to a new forecast by research and advisory firm Gartner.
The findings, released on October 14, 2026, highlight concerns over whether revenue generated from enterprise and consumer AI services will be sufficient to support the capital being invested in data centres, computing infrastructure and related technologies.
Gartner estimates that AI providers will spend nearly $1 trillion on infrastructure in 2026, followed by an additional $6 trillion between 2027 and 2030.
However, the research firm expects a substantial gap between infrastructure investment and the revenue available to support it.
According to Gartner, AI data centre operators would need to generate approximately $8.5 trillion in cumulative revenue through 2030 to cover announced capital expenditure, financing costs and a 12% return on invested capital.
In comparison, the firm forecasts that enterprise and consumer AI revenue attributable to AI data centres will reach no more than $3.6 trillion during the same period.
Will Sommer, Senior Director Analyst at Gartner, said the projected revenue would be insufficient to support profitable returns across all planned AI infrastructure investments.
The report also noted that many AI-native companies operate asset-light business models, meaning a significant proportion of AI revenue may not directly reach the companies owning and operating the underlying infrastructure.
Gartner expects fewer than half of AI revenues to be earned by providers with substantial infrastructure ownership.
The financial imbalance could result in asset write-downs, particularly as AI hardware depreciates and newer generations of semiconductors replace existing systems.
Under Gartner's projections, more than $4 trillion in infrastructure asset value could face write-down risks through 2032. The firm does not expect the assumed 12% return on invested capital to be achieved before the end of 2032.
The research also identifies neocloud providers, companies offering specialised AI computing infrastructure and cloud services, as particularly exposed to financial pressure.
Unlike large hyperscale cloud providers, which operate diversified businesses, neocloud companies depend more heavily on revenue from AI computing services.
Gartner predicts that more than 80% of neocloud providers could cease operating independently by 2030 because of cost pressures and limited differentiation.
The firm forecasts that spending on AI-optimised infrastructure as a service will increase from $66 billion in 2027 to $174 billion in 2030.
Despite this growth, Gartner expects revenue generation to remain insufficient for many providers to recover their infrastructure investments before existing hardware becomes obsolete.
The projections indicate potential consolidation across the AI infrastructure market as providers assess capital requirements, operating costs and long-term profitability.
Gartner's estimates are conditional forecasts rather than confirmed financial losses, with the eventual outcome dependent on infrastructure spending, AI adoption and revenue growth.
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