Resistance or resilience? University music teachers' active learning intention in response to the emergence of artificial intelligence

This study examines Chinese university music teachers' responses to AI integration using structural equation modeling (N = 317). Through Conservation of Resources (COR) theory, we investigate relationships between technology impact awareness, job insecurity, proactive personality, and active learning intention. Results reveal a "technology impact-job insecurity decoupling effect": technology awareness directly motivates learning (β = 0.519, p < 0.001) without triggering job insecurity as mediator. While job insecurity positively influences learning intention (β = 0.338, p < 0.001), it does not mediate the technology-learning relationship. Proactive personality moderates the insecurity-learning link (β = 0.132, p < 0.001). To explain this decoupling, we propose an "art-technology cognitive separation" mechanism whereby music teachers perceive AI as an auxiliary tool enhancing rather than threatening their artistic core. These finding challenges traditional assumptions that technological threats necessarily induce occupational anxiety before motivating adaptation. The study extends COR theory to creative professions and suggests institutions should focus on increasing AI awareness through opportunity-framed exposure rather than threat-based messaging, while tailoring support strategies to teachers' personality traits.