Cross-sectional survey reveals digital readiness and positive attitudes drive AI adoption among music learners, suggesting psychological factors outweigh formal musical background.
The increasing use of artificial intelligence (AI) in music education and creative production has introduced new opportunities for music learners to compose, arrange and refine musical works through AI‐assisted technologies. However, music learners differ considerably in their acceptance and intended use of these tools. This study examined the relationships among music learners' attitudes towards AI‐generated music, technology comfort level, technical expertise in music, frequency of AI tool usage and intention to adopt AI tools for future music creation. A quantitative survey was conducted with 543 Chinese music learners enrolled in universities, music conservatories and private training institutions. The data were analyzed using descriptive statistics, Pearson correlation analysis and multiple regression analyses. The findings revealed that positive attitudes towards AI‐generated music significantly predicted both the frequency of AI tool usage and learners' intention to adopt AI technologies in future music production. Technology comfort level also showed a significant positive association with adoption intention, indicating that greater confidence in using digital technologies facilitates acceptance of AI‐assisted music tools. In contrast, technical expertise in music demonstrated only a modest relationship with AI tool usage and had little influence on attitudes or future adoption intentions. Furthermore, age and formal music education did not significantly predict intention to adopt AI tools. Overall, the findings suggest that psychological factors and digital readiness play a more influential role than demographic or educational characteristics in shaping music learners' engagement with AI‐assisted music creation. The study contributes to the growing literature on AI in music education by identifying key factors associated with the acceptance and adoption of AI technologies among music learners and offers practical implications for music educators, curriculum developers and designers of AI‐supported music production systems.
No takes yet. Share an insight, caveat, or question.
Peng Cui (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: