Do companies that employ STEM and highly educated workers invest more in AI? And if so, how does it affect the hierarchical structure of the firm?
Anastassia Fedyk of the Haas School of Business at UC Berkeley joined us on Monday, May 9, 2022, to share her research.
A free, virtual event. In-person attendance is open to the Stanford community.
We study the shifts in U.S. firms’ workforce composition and organization associated with the use of AI technologies. To do so, we leverage 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. We document 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 and analysis 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, our results highlight that adoption of AI technologies is associated with significant reorganization of firms’ workforces.
Anastassia Fedyk is an Assistant Professor of finance at the Haas School of Business. Her research focuses on behavioral biases in individual and group decision-making, particularly concerning information and belief formation. She studies how information from a variety of sources, including financial news and individual employment records, influences asset prices. Fedyk holds a PhD in Business Economics from Harvard University and a BA in Mathematics with honors from Princeton University. Prior to pursuing her academic career, she was a researcher and portfolio manager at Goldman Sachs Asset Management.