BENGALURU: More than $3.5 trillion in artificial intelligence (AI) infrastructure spending could face financial write-downs by the end of 2030 if companies keep investing at their current pace, according to research firm Gartner.
AI providers are expected to spend nearly $1 trillion on infrastructure in 2026, followed by another $6 trillion between 2027 and 2030. However, Gartner warns that AI service revenue may not generate profitable returns on these investments.
“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, 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.”
AI infrastructure includes data centres, computing equipment and specialised chips used to develop and run AI systems.
Gartner estimates that owners of AI data centres would need to generate a combined $8.5 trillion in revenue by the end of 2030 to cover announced investment, financing costs and a 12% return on invested capital.
However, revenue from enterprise and consumer AI services that can be attributed to AI data centres is forecast to reach no more than $3.6 trillion during the same period.
“However, total enterprise and consumer AI revenue that can be attributed to AI data centers during this period is forecast to reach no more than $3.6 trillion,” Sommer said.
Gartner warns that companies could face financial losses if their investments fail to generate sufficient returns. This could force them to reduce the recorded value of their infrastructure assets, a process known as a write-down.
Under its projections, more than $4 trillion in AI infrastructure asset value could be exposed to write-down risk through 2032. Gartner does not expect a 12% return on invested capital to be achieved before the end of 2032 at the earliest under this scenario.
Neocloud providers, which offer computing infrastructure designed for AI workloads, are expected to face particular pressure.
Unlike large cloud companies, which have diversified sources of revenue, neocloud providers depend on generating sufficient returns from AI-focused infrastructure and related platforms.
Gartner forecasts that spending on AI-optimised infrastructure as a service (IaaS) will rise from $66 billion in 2027 to $174 billion in 2030. IaaS allows businesses to rent computing resources rather than build their own infrastructure.