This study investigates how leaders' AI-oriented change behavior affects employee-AI collaboration through employees' emotional responses using a double-edged sword framework. Drawing on the job demand-resource (JD-R) model and the conservation of resources (COR) perspective, this study highlights the moderating role of the perceived rarity of AI identity and explains the gain versus loss pathways.
Data were collected from 252 employees in China across two waves, with a three-week lag. Structural equation modeling using path analysis was conducted in Mplus 8.3 to examine the proposed mediation and moderation model.
Leaders' AI-oriented change behavior positively influences employee-AI collaboration by enhancing self-assurance and negatively by increasing workplace anxiety. The perceived rarity of AI identity amplifies both the positive and negative indirect effects.
This research integrates JD–R with COR to theorize resource-based emotional mechanisms in AI-driven change, and identifies perceived rarity of AI identity as a novel boundary condition. It clarifies leadership's resource-linked emotional pathways in promoting human–AI collaboration.
