AI Revenue Won't Cover Infrastructure Spending, Gartner Forecasts Trillion-Dollar Shortfall

Gartner Forecasts Trillion-Dollar AI Revenue Gap

Gartner has concluded that AI services are unlikely to deliver enough revenue to cover the expected capital expenditure going into IT infrastructure between now and 2030. The research firm's report, "Prepare for AI Market Consolidation: Capital Write-Downs Could Exceed $4 Trillion by 2032," finds that AI will not generate enough sales to profitably cover all planned AI capital spending before 2032 at the earliest.

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

The gap is substantial. Assuming a 12 percent return on invested capital, which many companies regard as the bar for acceptability, Gartner estimates AI datacenter operators would need to generate a total of $8.5 trillion in revenue to cover capital spending and financing costs while achieving that return. Instead, it forecasts that total enterprise and consumer AI revenue attributable to AI datacenters during this period will add up to no more than $3.6 trillion.

Neoclouds Face Existential Threat

The shortfall could force operators to write down assets whose value they can no longer recover, particularly as newer GPUs displace older hardware. Gartner expects the result to be a significant shake-out among companies providing AI infrastructure services, with neocloud operators, which are GPU-as-a-service providers specializing in AI compute, being the hardest hit.

Gartner forecasts that 80 percent of neocloud operators will not survive as independent companies beyond 2030. Sommer noted that not everyone is in trouble, adding that some will outperform, some will underperform, and some will have to exit the market. The hyperscalers are expected to weather the shake-out better because their businesses extend beyond AI services.

Last year, McKinsey and Company warned that neocloud companies need to move up the AI stack and diversify to avoid being commoditized.

Financial Markets Grow Wary

There has been growing unease in the financial markets over the amount of capital expenditure being poured into AI investment, with some money lenders starting to get cold feet. Last month, SoftBank Group faced higher borrowing costs as the tech investment business sought to drum up further funding for OpenAI.

Financial firm Jefferies issued a report this week saying that developers such as OpenAI and Anthropic are facing threats to their profitability from open source and Chinese models that undercut them on price. Management consultant Bain and Company also published a report last month estimating that the AI industry needs to generate $6 trillion in annual revenue by 2031 to keep up funding for the infrastructure needed to meet anticipated demand. Bain also forecast a revenue shortfall unless the industry develops products and use cases not yet identified.

Both the IMF and the Bank for International Settlements have voiced concerns about the AI bubble bursting and the effects rippling out across the global economy.

Sources: The Register