Against the background of the in-depth integration of artificial intelligence (AI) technology into various industries and the accelerated intelligent transformation of the global sports industry, graduates from sports vocational colleges are facing the dual pressure of upgraded job demands in the sports industry and insufficient matching of their own professional skills and comprehensive literacy. Focusing on the employment dilemma of graduates from sports vocational colleges, this paper adopts the methods of literature review, questionnaire survey and semi-structured interview to explore the practical value and application path of AI empowering the employment of graduates from sports vocational colleges. Based on the analysis of the current situation of AI application in the employment guidance, talent training and job matching of sports vocational colleges, this paper points out the existing problems such as insufficient application depth, weak AI literacy of teachers, lack of AI application ability of graduates and imperfect school-enterprise collaborative empowerment mechanism. Combined with the real demand of the intelligent sports industry for technical and skilled talents, targeted solutions and empowerment paths are proposed to provide theoretical support and practical reference for promoting the high-quality employment of graduates from sports vocational colleges, optimizing the employment work system of sports vocational colleges and promoting the coordinated development of the sports industry and vocational education. The research shows that AI technology can effectively break through the bottlenecks of homogenized employment guidance, inefficient job matching and backward talent training in sports vocational colleges, and help graduates improve their employment competitiveness. The organic integration of AI technology and the employment work of sports vocational colleges can effectively bridge the gap between talent training and enterprise demand, and promote graduates to achieve high-quality employment.
Zhang et al. (Sat,) studied this question.