Artificial Intelligence as a Catalytic Mechanism: A Theoretical Framework and Practical Pathways for Reshaping the Industry-Education Integration Ecosystem

This study aims to explore the transformative role of Artificial Intelligence (AI) in deepening Industry-Education Integration (IEI). Facing the rapidly changing skill demands of the AI era, traditional IEI models are bottlenecked by information asymmetry and slow responsiveness. This paper introduces the "Catalytic Mechanism" perspective, arguing that AI is not merely an efficiency tool but rather a force that reshapes the static partnership between industry and education into a self-optimizing, symbiotic ecosystem by reducing transaction costs and accelerating system responsiveness. This paper constructs a theoretical framework comprising three pillars: (1) AI-based dynamic skills mapping and curriculum reconstruction; (2) personalized learning pathways and career navigation; and (3) an intelligent collaborative ecosystem and value co-creation. The explanatory power of this framework is validated through a comparative case analysis of a university-led regional model and a corporate-led global model. The study finds that AI effectively overcomes the structural barriers of traditional models. Concurrently, it identifies challenges brought by AI integration, such as data privacy and algorithmic bias, and provides governance references for building a human-centric, AI-driven new paradigm for IEI, combining Chinese contexts with transnational comparative perspectives.