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.
