What public filings reveal about who funds AI data centers and who bears the risk, and what oversight should look like Stijn Van Nieuwerburgh's “Financing the AI Buildout” paper describes an investment cycle of nearly $9 trillion over 2025–32 that is increasingly funded through leases, joint ventures, project bonds, private credit and special-purpose vehicles. These structures expand funding capacity, but they also raise leverage at the level of the asset and keep much of it off the balance sheets of the firms that use the capacity. The template is Meta's Hyperion campus in Louisiana. A joint venture, 80 percent owned by Blue Owl funds and 20 percent by Meta, owns the campus and leases it back to Meta; Beignet Investor, the Blue Owl vehicle that holds the 80 percent stake, sold about $27 billion of bonds to pay for it. The paper's central worry is that the resulting exposures are layered, correlated and hard to observe. This post asks how hard. I tried to map the fina...
Most of the debate about AI and labor markets is a debate about workers. Almost none of it is about the entity standing quietly behind every payroll. Moving from employment-share exposure to labor-tax-revenue exposure changes which occupations matter — and which policies do. Results draw on ongoing joint work with Dhushyanth Raju applying the Richmond (2026) AI transition framework to Türkiye's 2024 Household Labour Force Survey Most of the debate about AI and labor markets is a debate about workers: who gets displaced, who gets augmented, who gets retrained. Almost none of it is about the entity standing quietly behind every payroll: the treasury. Governments in most middle- and high-income countries raise roughly half of their revenue from labor — personal income tax plus social security contributions. If AI-driven capital deepening shifts factor income from labor toward capital, that base erodes at precisely the moment demand for social spending r...