Columbia Business School report outlines $3.7T revenue needs for AI data centers

Building the infrastructure for artificial intelligence is going to cost roughly $10.3 trillion in the United States alone between 2025 and 2032. And to make that investment pencil out, the AI sector needs to generate approximately $3.7 trillion in annual revenue by the end of that window. Those figures come from Columbia Business School professor Stijn Van Nieuwerburgh, whose analysis was presented at the Brookings Papers on Economic Activity conference. The study attempts to answer a question that has been quietly nagging anyone paying attention to the AI buildout: does the math actually work? The numbers behind the buildout The core projection calls for adding approximately 182.7 gigawatts of data center capacity by 2032. For context, that’s a staggering amount of power infrastructure, roughly equivalent to about 3.63% of US GDP annually in investment spending. To put the scale in perspective, the report notes this buildout would surpass historical infrastructure investments like the construction of the railroad network and the interstate highway system. The per-unit economics tell an equally demanding story. The analysis estimates that profitability requires about $5.5 in reven...