A new MIT study using a large-scale labor simulation found current AI systems can economically and technically perform work equal to roughly 11.7% of U.S. jobs, a finding that has direct implications for academic staffing and campus operations. The Project Iceberg model—built with Oak Ridge National Laboratory—maps 32,000 skills across occupations and estimates about $1.2 trillion in wage exposure where AI is already cost‑competitive. Researchers stress this is a measure of feasibility, not a timetable, but warn universities should plan for rapid shifts in administrative roles, entry-level positions and some research tasks.