Reform Path of Talent Training Model in Local Universities under the Background of Artificial Intelligence

At present, local universities are facing problems such as outdated teaching models, lagging discipline settings, and weak integration of industry, academia and research, making it difficult to adapt to the rapid development of artificial intelligence (AI).This study explores the path of talent training model reform in local universities under the background of AI.Through literature review and field research, this study analyzes the challenges faced by universities and proposes the necessity of reform.The research methods include case analysis, interviews with education experts and business people, evaluating the fit between the existing curriculum system and AI technology, promoting the integration of industry, academia and research, setting up interdisciplinary innovative courses, and strengthening teacher training and international exchanges.The results show that after the reform, universities have significantly improved in curriculum setting, faculty strength, scientific research level and employment rate.More than 60% of graduates have entered AI-related industries, and the employment rate and course satisfaction have significantly improved.Research shows that strengthening AI course offerings can help local universities enhance their competitiveness in the era of artificial intelligence and provide stronger intellectual support and innovation drive for social and economic development.