When Generative Artificial Intelligence Becomes a Colleague: Dual Pathways of Empowerment and Depletion in University Design Teachers’ Work Behaviors

As generative AI (GAI) becomes increasingly embedded in higher education teaching, its influence on teachers’ instructional behaviors has shown complex and even contradictory patterns. Moving beyond the dominant single-path perspective that emphasizes technological empowerment, this study integrates Conservation of Resources theory and Social Exchange Theory to develop a dual-path framework explaining how GAI simultaneously enables and depletes teachers’ psychological resources. Using survey data from 436 university design teachers in mainland China, structural equation modeling and conditional process analysis were employed. The results indicate that GAI use enhances teaching self-efficacy and teaching-related well-being, thereby promoting innovative work behavior and reducing work withdrawal through a resource-enabling pathway. Conversely, GAI use also increases AI-related anxiety and teaching-related occupational stress, forming a resource-depleting pathway that suppresses innovation and intensifies withdrawal tendencies. Further analyses show that perceived organizational support strengthens the positive effects of GAI, whereas psychological contract breach amplifies its negative impacts. These findings extend research on teacher behavior in educational technology contexts and offer practical insights for fostering supportive environments and mitigating psychological costs during GAI integration.