Where Work Is Moving Occupations, Academic Programs and Places in the 2035 AI Workforce Scenario: A Roadmap for Higher Education

The McKinsey Global Institute (MGI) estimates that, by 2035, automation could reduce U.S. labor demand by about a fifth of current work hours, while broader growth creates more jobs than automation removes. About 11 million workers may need to change occupations in the next decade. Colleges and universities plan programs years ahead, so they need to know what this scenario means for the programs they offer and the places they serve. We translate the MGI scenario into estimates for 830 detailed occupations, 1,432 academic program families at four award levels, and 530 metropolitan and nonmetropolitan areas. A task-level model of AI adoption, built from language-model exposure, observed AI success and review time, the cost of errors and governance, distributes MGI's totals across occupations. We also report the model's independent estimate and explain where and why it differs from MGI. Almost no occupation disappears: one falls by more than half and 62 fall by 20–50%. About 9.5 million jobs are in occupations that decline, almost half of them in office and administrative support. Program risk sits below the bachelor's degree. About 8% of certificate and 7% of associate completions are in programs whose graduates' occupations shrink by 10% or more, while 48% of certificates and 32% of associate degrees are in programs whose fields grow by 10% or more. At the bachelor's and graduate levels demand is broadly stable, but AI is expected to adopt or augment more than half of graduates' work hours, so the task is curriculum reinvention rather than closure. The need to change jobs is greatest in rural, agricultural and lower-wage areas; the wages at stake are greatest in high-wage hubs. We set out a roadmap for investment, reinvention, consolidation and review.