Columbia University professor estimates AI spending may hit $3.5T by 2032

Columbia University: Columbia University is a leading Ivy League research institution with prominent business and engineering schools focused on economics, finance, and emerging technologies. Its faculty contribute to high-profile studies on macroeconomic trends and innovation. Professor Stijn Van Nieuwerburgh from its Business School recently authored key research on AI infrastructure financing presented at a Brookings conference. Stijn Van Nieuwerburgh: Stijn Van Nieuwerburgh is the Earle W. Kazis and Benjamin Schore Professor of Real Estate at Columbia Business School, with expertise at the intersection of finance, real estate, and macroeconomics. He recently presented a Brookings paper analyzing the financing structures and risks of the U.S. AI data center buildout. His work emphasizes uncertainties around revenue generation supporting large-scale investments in the sector. Revenue Uncertainty: Uncertain demand and rapid technological change in AI create potential downside risks if expected returns on infrastructure investments fail to materialize. Historical Comparison: The scale of current AI-related capital commitments exceeds the relative economic intensity of past major U.S. infrastructure expansions such as railroads or highways. AI Financing Complexity: AI infrastructure projects increasingly rely on intricate arrangements involving project finance, private credit, and special purpose vehicles rather than traditional corporate balance sheets.