arXiv · 2610.08264
Understanding Interfirm AI Talent Flow Networks through Online Professional Profiles
Abstract
Artificial intelligence capabilities are often measured as resources accumulated within firms, yet they also circulate across organizational boundaries through worker mobility. Drawing on a database of approximately 535 million employment records across 58 countries, we reconstruct the inter-firm network of AI talent flows over 2010--2022. We find that AI talent inflows are becoming increasingly concentrated among a small set of leading firms, with stronger preferential attachment than in general labor mobility. Yet the network core remains contestable: central positions in AI networks change hands far more often than in non-AI networks. Network position also carries information that goes beyond workforce size. This network position is economically consequential: AI network centrality is associated with higher enterprise value, after accounting for workforce scale, assets, and fixed effects. Event-study estimates further indicate that sharp improvements in network position are followed by higher enterprise value relative to matched firms with similar pre-event trajectories. Together, these findings suggest that corporate AI advantage depends not only on how much talent firms accumulate, but also on where they sit in its circulation.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Donghang Li, Yunhan Zheng, Alok Prakash, Shenhao Wang, Jinhua Zhao. 2026-10-06. Understanding Interfirm AI Talent Flow Networks through Online Professional Profiles. https://arxiv.org/abs/2610.08264
Cite the original work for its findings. Save a collection to share your selection of sources.