To justify today’s data center buildout, AI would need to bring in about $3.5 trillion a year by 2032, per a new Brookings paper. That’s 8.8% of U.S. GDP, nearly as much as Americans spend on food (9.1%), and far more than on energy (5.1%).

A new Brookings paper estimates that AI would need to generate roughly $3.5 trillion in annual revenue by 2032 to justify the current pace of data center investment, equal to about 8.8% of U.S. GDP. The comparison points to food spending, which accounts for 9.1% of GDP, as a benchmark for how large that revenue requirement would be across the economy. The transmission channel is expectations: capital spending on data centers feeds into corporate earnings forecasts, equity valuations of AI-linked hyperscalers and semiconductor firms, and credit demand for utilities and energy infrastructure that must supply power to these facilities. Energy and utility equities, along with high-grade corporate bonds issued to fund buildouts, are most exposed if revenue growth lags the capex trajectory, since their valuations and financing assumptions depend on sustained data center demand. Traders should watch the next quarterly capital expenditure guidance from major cloud providers and any subsequent AI revenue disclosures, which will indicate whether the spending gap the paper describes is narrowing.

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