The Intersection of Music Learning, Artificial Intelligence, and Occupational Health: A Job Demands-Resources Analysis of Technostress, Burnout, and Engagement Among Music Students

This study applies Job Demands-Resources (JD-R) theory to music student psychology, with particular attention to the differentiated impacts of artificial intelligence across music student subgroups. Background: Music education requires intensive cognitive, motor, emotional, and social training. Methods: Employing a narrative literature review and conceptual framework approach, this paper draws on JD-R theory, technostress research, and cross-cultural scholarship to identify demands and resources in music education and examine their relationships with burnout and engagement. Results: Seven demands: technical, physical, temporal, performance, social–emotional, technostress, cultural identity. Resources: teacher support, peer collaboration, instruments, AI tools, curricula, and intrinsic motivation. Critically, AI-related demands and resources differ substantially across subgroups: composers face direct demand shocks (job displacement) and resource opportunities (creative augmentation) that vary by career stage, while performers experience more indirect impacts through recording market disruption and emerging self-media opportunities. Singers face a unique paradox whereby AI voice cloning creates short-term recording opportunities while potentially enabling long-term vocal replacement. Cultural identity demands arise from heritage-Western tensions in East Asia. Conclusions: This JD-R framework provides a nuanced lens for understanding music students’ well-being that accounts for subgroup-specific vulnerabilities and opportunities.