Against the backdrop of industrial digital transformation and higher education reform, advancing industry-education integration is a critical pathway for applied undergraduate institutions to cultivate high-quality applied talent. However, practical implementation faces significant challenges, such as inadequate university-enterprise cooperation mechanisms and a shortage of “dual-qualified” faculty. This study integrates data from 20 universities and 50 enterprises, drawing on 1,200 questionnaires (with an 83.3% valid response rate), 20 in-depth interviews, and case analyses. It develops a “Quadruple Dynamic Coupling Theory Model” and designs a “Government-Industry-University-AI” collaborative framework incorporating AI solutions. Practical implementation demonstrates that AI integration enhances school-enterprise collaboration efficiency by 42% and achieves an 89% satisfaction rate in dual-qualified instructor training. These findings provide valuable insights for optimizing industry-education integration practices at applied undergraduate institutions and contribute to refining relevant theoretical frameworks.

Yuhui Chen, Biao Zhang, Runfa Li, Li Chen, Pei Lv. AI-Empowered Industry-Education Integration: Overcoming Challenges and Reconstructing Collaborative Pathways in Applied Undergraduate Institutions. Frontiers in Educational Research (2025), Vol. 8, Issue 12: 29-34. https://doi.org/10.25236/FER.2025.081205.

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