Gartner Forecasts More Than $3.5 Trillion of AI Infrastructure Spending Could Face Write-Downs by 2030

More than $3.5 trillion of spending on artificial intelligence (AI) infrastructure could have to be written down by the end of 2030, if AI providers keep spending at their current pace, the research firm Gartner forecast on 14 October 2026.

A write-down, or impairment, is when a company admits an asset is worth less than it paid and cuts its value on the books. Gartner says the money AI is forecast to earn will not be enough to justify everything being built.

Gartner also predicts that by 2030, cost pressure and a lack of a distinctive business model will force over 80% of neocloud providers, companies that rent out AI computing power, to stop operating independently.

The forecast gap

“In 2026, AI providers are expected to spend nearly $1 trillion on AI infrastructure, and are forecast to invest an additional $6 trillion between 2027 and 2030,” said Will Sommer, a senior director analyst at Gartner. “However, our research indicates that enterprise and consumer AI revenue will be insufficient to support profitable returns on all planned AI capital expenditures during this period.”

According to Gartner’s projections:

• Revenue needed: AI data centre owners would need to earn a combined $8.5 trillion by 2030 to cover announced spending, financing costs and a 12% return on invested capital, which Gartner assumes is the minimum return investors expect.
• Revenue forecast: AI revenue that can be linked to AI data centres over the same period is forecast to reach no more than $3.6 trillion.
• Who earns it: Gartner predicts less than half of AI revenue will go to providers that own significant AI infrastructure, because most AI-native companies rent rather than own.
• Longer term: if investment continues on its current path, more than $4 trillion in asset value could be at risk of write-down through 2032. In that scenario, Gartner does not expect the 12% return to be reached until the end of 2032 at the earliest.

Why neoclouds are most exposed

Gartner says neoclouds will be among the most exposed. Hyperscalers such as the big cloud companies have “massive and highly diversified revenue sources that could plausibly sustain AI investments for years,” it said, while neoclouds need to earn returns soon.

Gartner forecasts spending on AI-optimised cloud infrastructure will grow from $66 billion in 2027 to $174 billion in 2030. “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,” Sommer said.

He told The Register that the picture is mixed: “Not everyone is in trouble. Some will outperform, some will underperform, and some will have to exit the market.”

What this means

• This is a forecast, not a verdict. The numbers are Gartner’s projections and depend on spending continuing at today’s pace.
• AI may not pay for itself quickly enough. Gartner forecasts a gap of trillions of dollars between spending and revenue.
• Expect consolidation. Gartner predicts most neoclouds will be bought, merged or shut by 2030.

Sources

1. Gartner, “Gartner Says Over $3.5 Trillion of AI Infrastructure Spending Could Be Exposed to Impairment by the End of 2030”, 14 October 2026. https://www.gartner.com/en/newsroom/press-releases/2026-10-14-gartner-says-over-us-dollars-three-and-a-half-trillion-of-artificial-intelligence-infrastructure-spending-could-be-exposed-to-impairment-by-the-end-of-2030
2. The Register (Dan Robinson), 14 October 2026. https://www.theregister.com/on-prem/2026/10/14/ai-math-isnt-mathing-infrastructure-spending-forecast-to-outstrip-expected-revenue/5302856

Related stories

• Volta Launches a $5.012bn Six-Year Loan, PitchBook Reports; It Is Launch-Stage Pricing, Not a Closed Deal
• IMF Names an AI Market Correction, Rising Bond Yields and Cyberattacks as Near-Term Risks to Financial Stability
• Broadcom and Intel Bosses Say Money, Not Chips, May Be AI’s Biggest Constraint; Intel’s Chief Calls Chinese Model Uptake “Very Fast”
• Microsoft’s Azure Chief Reportedly Asked Leaders to Find at Least 20% in Cost Cuts; Microsoft Disputes the Report