Gartner warns that over $3.5 trillion in AI infrastructure spending faces impairment risk by 2030 if current capital expenditure trends continue. While AI data center owners must generate $8.5 trillion by 2030 to cover costs and achieve a 12% return on invested capital, projected revenue is capped at $3.6 trillion. Gartner expects over 80% of neocloud providers to cease operations under cost pressures, while hyperscalers rely on diversified revenue to sustain investment.
AI infrastructure spending forecasts
- ▪Gartner forecasts that a continued AI infrastructure investment trajectory puts over $3.5 trillion of spending at impairment risk by the end of 2030 and more than $4 trillion in asset value at write-down risk through 2032
- ▪Gartner forecasts that AI providers will spend nearly $1 trillion on AI infrastructure in 2026 and an additional $6 trillion between 2027 and 2030
- ▪Gartner estimates that spending on AI-optimised Infrastructure as a Service will grow from $66 billion in 2027 to $174 billion in 2030
Data centre revenue and return shortfalls
- ▪Gartner projects total enterprise and consumer AI revenue attributed to AI data centres through 2030 to cap at $3.6 trillion, covering less than half of required investment returns
- ▪Gartner projects that a 12% return on invested capital for AI data centre owners will not be achieved until the end of 2032 at the earliest
- ▪Gartner reports that AI data centre owners must generate a cumulative $8.5 trillion in revenue through 2030 to cover announced capital spending, financing costs, and a 12% return on invested capital
Neocloud provider vulnerabilities
- ▪Gartner states that while hyperscalers have diversified revenue sources to sustain AI investments, neoclouds depend on earning immediate returns from AI-optimised platforms to survive
- ▪Gartner predicts that over 80% of neocloud providers will cease operations due to cost pressures and a lack of differentiating business models
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