From signals to action: how digital leadership, AI skills and knowledge sharing culture shape employees’ digital-intelligence transformation

Abstract

Drawing on the job demands–resources model and the stimulus–organism–response framework, this study examines how organizational signals and artificial intelligence–enabled work conditions shape employees’ intention and behavior in supporting digital-intelligence transformation. Data were collected through a three-wave time-lagged survey of 316 employees from high-technology enterprises and analyzed using structural equation modeling and response surface analysis. The results show that digital leadership and artificial intelligence digital assistant skills strengthen employees’ digital-intelligence mindset and digital-intelligence self-efficacy, which in turn promote supportive intention and behavior. Knowledge sharing culture exhibits weaker and partially negative effects on readiness. Alignment between mindset and self-efficacy enhances supportive outcomes, whereas misalignment undermines supportive intention. In addition, artificial intelligence and robotics awareness amplify the effect of self-efficacy on supportive intention. The findings highlight the importance of employee readiness configurations in artificial intelligence–enabled transformation contexts. This study advances microfoundational understanding of digital-intelligence transformation by integrating readiness alignment and boundary conditions into an employee-centered model.