How AI Leadership Stimulates Employees' Proactive Innovation Behavior: A Model with Self-Efficacy as a Mediator

Abstract

Against the backdrop of digital-intelligent transformation, the deep integration of AI into organizational management has given rise to AI leadership as a new leadership paradigm. Drawing on social cognitive theory, this study examines how AI leadership affects employees' proactive innovation behavior through self-efficacy and whether cognitive flexibility serves as a boundary condition. Data were collected from 170 employees through an online survey and analyzed using hierarchical regression and Bootstrap tests. The results show that AI leadership significantly and positively predicts proactive innovation behavior, while self-efficacy partially mediates this relationship by strengthening employees' confidence in digital technology use and innovation. The hypothesized moderating effect of cognitive flexibility is not supported. The study extends social cognitive theory to human-AI collaborative management and clarifies a micro-level cognitive pathway through which AI leadership promotes employee innovation.