Research on the Collaborative Development Path of AI Teaching and Industry-Education Integration of Intelligent Manufacturing Specialty Groups in Higher Vocational Colleges

Abstract

With the in-depth advancement of the new round of technological revolution and industrial transformation, the intelligent manufacturing industry is accelerating its digital and intelligent transformation, leading to a growing market demand for high-quality compound technical and skilled talents with practical capabilities. The full-scale empowerment of artificial intelligence (AI) technology has restructured the talent training logic of higher vocational education and promoted the iterative upgrading of traditional teaching paradigms. As the core carrier for higher vocational colleges to connect with the advanced manufacturing industry, the in-depth collaboration and two-way empowerment between AI teaching reform and industry-education integration are critical to resolving the structural mismatch between talent training and industrial demands and improving education quality. Adopting the research methods of literature review, comparative analysis and case study, this paper systematically sorts out domestic and foreignresearchfindingsandpracticalparadigms,andanalyzesthekeyproblemsrestrictingcollaborative development, including superficial integration, lagging curriculum system iteration, insufficient compound teachers, and imperfect long-term guarantee mechanisms. By constructing a multi-dimensional comparative model, this paper evaluates the advantages, disadvantages and applicable scenarios of differentAI teaching and industry-education integration modes. On this basis, a systematic collaborative development path is constructed from four dimensions including concept reconstruction, system optimization, mechanism innovation and resource guarantee, providing theoretical support and practical