The AI industry is building like it expects to become a pillar of the economy. A new Brookings paper has worked out what that would actually take. The estimate: AI must generate about $3.5 trillion a year by 2032 to justify the current data center expansion. The paper’s detailed math lands even higher, at approximately $3.725 trillion annually. The math behind the buildout The paper comes from Stijn Van Nieuwerburgh of Columbia Business School. It was published through the Brookings Papers on Economic Activity, better known as BPEA. Van Nieuwerburgh estimates US AI infrastructure investment will total $10.3 trillion between 2025 and 2032. That works out to an average of 3.63% of GDP every year. The paper finds this spending notably surpasses earlier US infrastructure booms, including the railroads and the interstate highways. The paper uses a 10% unlevered return as its benchmark. To hit that bar, the AI sector would need roughly $3.725 trillion in annual revenue by 2032. That would equal approximately 9% of projected US GDP in that year. From $100 billion to trillions OpenAI and Anthropic, the two best-known AI labs, currently bring in about $100 billion in combined revenue, accor...
Brookings paper says AI needs trillions in annual revenue by 2032 to pay for its data centers
2 weeks ago
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