Game Theory Research on the Development and Promotion of Artificial Intelligence Teaching Platform Based on Multi-Participant University-Enterprise Collaboration

With the deep integration of artificial intelligence and education, university-enterprise cooperation has become a key approach for the development and promotion of artificial intelligence (AI) teaching platforms. However, differences in the interests of various stakeholders lead to insufficient stability in cooperation. Therefore, based on evolutionary game theory, this study constructs a dynamic game model involving enterprises, universities, and teachers. By establishing a replicating dynamic equation, the equilibrium point is solved and its stability is analyzed. Numerical simulations are then used to explore the evolutionary mechanism of each stakeholder’s strategy and key influencing factors. The study finds that enterprise strategy selection is influenced by teacher feedback and university support; university decisions focus on long-term educational benefits; and teachers’ willingness to use the platform depends on the balance between learning costs and benefits. Simulation analysis shows that factors such as benefit structure, training costs, and financial rewards significantly affect the evolutionary trend. This research provides theoretical basis and practical insights for promoting industry-university collaboration and optimizing platform construction and promotion.