Gartner says $3.5 trillion in AI infrastructure spending could face impairment

Gartner said more than $3.5 trillion in AI infrastructure spending could be exposed to impairment by the end of 2030 if providers maintain their current pace of capital investment. The forecast concerns potential write-downs—reductions in the accounting value of assets—rather than losses that have already occurred.

Gartner expects AI providers to spend nearly $1 trillion on infrastructure in 2026, followed by another $6 trillion from 2027 through 2030. Under its model, data-center owners would need $8.5 trillion in cumulative revenue through 2030 to cover announced capital spending, financing costs and an assumed 12% return on invested capital. Gartner forecasts no more than $3.6 trillion in enterprise and consumer AI revenue attributable to those data centers over the same period.

That leaves a $4.9 trillion gap between Gartner’s revenue requirement and its maximum attributable-revenue forecast. The figure is a subtraction based on Gartner’s assumptions, not a separate estimate of realized losses. The firm also predicts that infrastructure owners will receive less than half of AI revenue because many AI-native providers use asset-light business models.

If the current investment trajectory continues, Gartner projects that more than $4 trillion in asset value could be exposed to write-down risk through 2032. It says the assumed 12% return would not be reached before the end of 2032 at the earliest.

Gartner expects the pressure to be especially severe among neoclouds, which it defines as cloud providers built for AI and high-performance workloads. The firm predicts that cost pressure and limited business-model differentiation will cause more than 80% of neocloud providers to cease operating independently by 2030. That is a consolidation forecast, not a completed outcome; the release does not quantify how many providers would fail outright.

“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,” Gartner senior director analyst Will Sommer said in the release. Gartner estimates that spending on AI-optimized infrastructure as a service will rise from $66 billion in 2027 to $174 billion in 2030.