Driving sustainable innovation outcomes through employee AI collaboration with the mediating role of sustainable career capacities

Amid digital transformation, artificial intelligence (AI) integration into organizational work has reshaped employee-technology interactions and career trajectories. Despite growing interest in Employee-AI Collaboration (EAC), there is little research examining its impact on both sustainable career development and innovation outcomes. Drawing on Conservation of Resources (COR) theory and Social Cognitive Theory (SCT), this study examines how EAC influences Sustainable Innovation Outcomes (SIO) via Sustainable Career (SC) capacities and the moderating effect of Self-Efficacy in Using AI (SEUA). Using a cross-sectional survey of 294 employees, we employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to test our hypotheses. Results show that EAC significantly enhances all the four SC dimensions: Resourceful, Flexible, Renewable, and Integrative capacities. These dimensions mediate the relationship between EAC and SIO, while EAC also exerts direct effects. Alternative model analysis suggests a mutually reinforcing relationship between SC and SIO. Notably, SEUA negatively moderates the relationship between EAC and the Integrative dimension, suggesting a counterintuitive attribution mechanism. These findings reveal how EAC drives innovation through both direct technological enhancement and indirect career capacity development pathways. This research extends technology empowerment theory into career development contexts, providing evidence-based recommendations for organizations to optimize AI integration strategies and career development policies.