Firm Investments in Artificial Intelligence Technologies and Changes in Workforce Composition
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 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.
This project did not receive external funding. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Forthcoming: Firm Investments in Artificial Intelligence Technologies and Changes in Workforce Composition, Tania Babina, Anastassia Fedyk, Alex X. He, James Hodson. in Technology, Productivity, and Economic Growth, Basu, Eldridge, Haltiwanger, and Strassner. 2023