In this talk, Tania Babina of Columbia Business School discusses her research in which she studied the shifts in U.S. firms’ workforce composition and organization associated with the use of AI technologies. To do so, she leveraged a unique combination of worker resume and job postings datasets to measure firm-level AI investments and workforce composition variables, such as educational attainment, specialization, and hierarchy. She documented that firms with higher initial shares of highly-educated workers and STEM workers invest more in AI. As firms invest in AI, they tend to transition to more educated workforces, with higher shares of workers with undergraduate and graduate degrees, and more specialization in STEM fields and IT skills. Furthermore, AI investments are associated with a flattening of the firms’ hierarchical structure, with significant increases in the share of workers at the junior level and decreases in shares of workers in middle-management and senior roles. Overall, her results highlight that adoption of AI technologies is associated with significant reorganization of firms’ workforces.
This talk is part of the Digital Seminar, a D^3 Assembly series that is open to faculty, doctoral students, and academic researchers.
Email us at d3ln@hbs.edu for information on attending this seminar.