When My Skill Becomes Agent Skill: How Knowledge Workers Share Their Expertise with AI Systems

2026-10-07

AI Summary

This study investigates how AI agent reuse influences knowledge workers’ willingness to share expertise. Employing a behavioral experiment, the research compares employees’ delegation decisions in human versus AI reuse scenarios and integrates a knowledge management framework with qualitative reasoning to analyze the evolution of underlying psychological motivations. The findings reveal that although the shared content remains comparable, exposure to AI reuse significantly shifts employee motivation from prosocial drivers toward concerns over diminished control, thereby intensifying conflicts between organizational interests and individual rights. This work elucidates the psychological mechanisms underlying the paradox of knowledge-sharing intentions in AI-mediated contexts and provides empirical evidence to inform AI governance policies designed to safeguard employee autonomy.

Abstract

Organizations have long sought to make workers' expertise reusable by others. Agentic AI changes the nature of such reuse by enabling AI systems to act on workers' knowledge with limited human involvement. This raises the question of how this shift shapes workers' willingness to share their expertise. We conducted an experiment with knowledge workers who created materials incorporating domain knowledge and decided whether to authorize human or AI reuse. We find that AI and human reuse differ primarily in whether workers choose to share their knowledge, rather than in what they choose to share. Participants' reasoning shifts from prosocial considerations when sharing with humans toward concerns about loss of control, replacement, and downstream governance when sharing with AI. These findings suggest that AI reuse may intensify tensions between organizational knowledge reuse and contributors' interests. We discuss implications for workplace AI and knowledge management policies that preserve workers' rights and agency.

Problem

• Agentic AI
• Knowledge Sharing
• Expertise Reuse
• Knowledge Workers
• Workplace AI

Innovation

• Agentic AI
• Knowledge Sharing
• Human-AI Interaction
• Knowledge Management
• Loss of Control