Artificial intelligence readiness and innovative work behavior among university engineering teachers: parallel indirect effects of creative self-efficacy and technology integration self-efficacy

Introduction Artificial intelligence (AI) is becoming part of university teachers’ teaching and research, yet its relationship with innovative work behavior in engineering education remains unclear. Methods Drawing on Social Cognitive Theory and Conservation of Resources Theory, this cross-sectional study surveyed 786 university engineering teachers in Chongqing, China. We examined the association between AI readiness and innovative work behavior and tested parallel indirect effects through creative self-efficacy and technology integration self-efficacy. Gender and educational attainment were included as covariates. Results AI readiness was positively associated with innovative work behavior. The indirect paths through creative self-efficacy and technology integration self-efficacy were both significant. AI readiness remained significantly associated with innovative work behavior after both mediators were included, indicating partial mediation. Discussion These findings suggest that AI readiness and efficacy beliefs may support innovative work among engineering teachers. Universities can support quality education by linking AI training to course design, laboratory teaching, project development, and research tasks, while using guided practice and feedback to build teachers’ confidence.