Employee–AI collaboration and employee innovative behavior: The roles of AI self-efficacy and AI trust

Purpose: In the era of digital transformation, employee–artificial intelligence (AI) collaboration has become an increasingly important work pattern. However, its impact on employees’ innovative behavior remains unclear. Drawing on the social cognitive framework, this study aims to examine how employee–AI collaboration influences employees’ innovative behavior and to uncover the underlying mechanism. Design/Methodology/Approach: A 2 × 2 scenario-based experiment was conducted among employees from China. The experiment manipulated two factors: the level of employee–AI collaboration (high vs. low) and the level of AI trust (high vs. low). Findings: The results indicate that employee–AI collaboration has a positive effect on employees’ innovative behavior. AI self-efficacy mediates the relationship between employee–AI collaboration and innovative behavior. In addition, AI trust moderates this relationship. Originality/Value: This study extends the research on human–AI collaboration to the domain of employee innovation and reveals the cognitive mechanism and boundary condition underlying the influence of employee–AI collaboration on innovative behavior.