AI infrastructure returns under pressure: Gartner expects over $3.5 trillion in investment to face impairment risk.

Beating AI News Flash: Gartner estimates that by 2030, AI data center owners will need to generate a cumulative $8.5 trillion in revenue to cover capital expenditures, financing costs, and achieve a 12% return on invested capital. However, revenue attributable to enterprise and consumer AI businesses during the same period is projected to be only $3.6 trillion, less than half of the target.

The firm warns that AI infrastructure investment expansion may outpace revenue growth, and rapid depreciation of computing assets could render them obsolete before generating sufficient returns. Over $3.5 trillion in AI infrastructure spending is estimated to face impairment risk.

Separately, Global X research estimates that AI-related revenue from 15 AI platform and service providers will surpass infrastructure depreciation around 2027 and reach approximately $1.5 trillion by 2030. The firm estimates that by 2030, every $1 of annual depreciation expense on AI-related assets will correspond to $2.36 in AI revenue. However, revenue covering depreciation does not mean it is sufficient to cover financing costs and meet the 12% return on capital requirement.

Gartner also predicts that cost pressures and insufficient business differentiation will cause more than 80% of new cloud service providers to cease independent operations by 2030. Meanwhile, CoreWeave's CEO stated that the company's backlog is sufficient to support its debt obligations. The company disclosed a revenue backlog of $104.2 billion in the second quarter and said new customer commitments in the third quarter exceeded $25 billion.