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arXiv · 2610.32461

The Effects of Generative AI on Collaboration and Social Networks Among Knowledge Workers

Giuseppe Soda·Alessandro Iorio·Leonardo Rizzo
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Abstract

The rapid diffusion of generative artificial intelligence has raised concerns that knowledge work may become less dependent on human-to-human interaction. Yet because AI-generated outputs require interpretation, verification, and social legitimation, generative AI may instead increase collaboration among workers. We test these competing predictions using passively collected behavioral data from more than 12,000 knowledge workers observed over 13 months during the staged organizational rollout of an AI-powered assistant (Microsoft Copilot). Using two complementary quasi-experimental designs -- a staggered difference-in-differences model and a fixed-effects instrumental-variable approach -- we estimate the effects of generative AI on workers' collaboration behavior and social network structure. We estimate that generative AI increased collaboration time across communication channels and reshaped individual networks. Those using generative AI interacted with more colleagues and their networks became less clustered, indicating broadening in collaboration structures. At the same time, they also concentrated more of their collaboration on ties with stronger prior histories, deepening reliance on already trusted colleagues. Together, these findings suggest that, while generative AI changes how people work, it may not displace human-to-human interactions.

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Giuseppe Soda, Alessandro Iorio, Leonardo Rizzo. 2026-10-23. The Effects of Generative AI on Collaboration and Social Networks Among Knowledge Workers. https://arxiv.org/abs/2610.32461

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