Psychological safety and AI adoption as antecedents of teaching burnout: the mediating effect of work–life balance

Purpose This study aims to investigate the relationship between the adoption of artificial intelligence (AI), psychological safety, work–life balance, and burnout in the teaching context. Furthermore, this study examines the relationship between AI adoption and the psychosocial dimensions of lecturers’ mental health. The findings aim to inform strategic decisions in human resource management and technology development within universities. Design/methodology/approach Based on the integration of Technology Acceptance Theory (TAM) and Conservation of Resources (COR) Theory, the research model was built and tested using the partial least squares structural equation modeling method. Data were collected from 487 lecturers working at universities in Vietnam. Findings The results indicate that AI adoption is positively associated with psychological safety and work–life balance. AI adoption is also significantly associated with burnout in teaching, both directly and through its association with work–life balance. Work–life balance is statistically related to both AI adoption and burnout in teaching, suggesting a mediating pattern within the proposed model. These associations highlight how psychological resources tend to co-vary as technology becomes more embedded in the educational environment. Originality/value The study contributes to theoretical understanding by integrating the two foundations of TAM and COR to explain the role of AI adoption on the mental health of lecturers in digital transformation. The study provides practical management insights for universities to implement AI technology effectively. This approach not only is related to performance but also protects the long-term mental and emotional well-being of lecturers.