Based on the background of digital transformation of education, the research constructs a three-stage implementation framework of ‘data governance - intelligent diagnosis – targeted intervention’ to address the homogenisation and sloppy learning cultivation in applied universities. Through the integration of artificial intelligence technology and educational innovation concepts, the implementation path of precise education is proposed innovatively: integrating multi-source data to build dynamic student profiles in the data governance layer; establishing stratified early warning and potential identification models in the intelligent diagnosis layer; and designing industry-education synergy and blended learning mechanisms in the targeted intervention layer. Specifically, the targeted intervention layer designs a tiered response intervention strategy through industry-teaching collaboration and blended learning mechanism, including the establishment of a three-level intervention strategy for academic crisis, potential stimulation, and special groups; the development of a system to match job competencies with course content; and the use of intelligent grouping system to improve the efficiency of teamwork. Practice shows that the path significantly improves the efficiency of academic crisis identification, shortens the transition cycle of students ‘transformation to professional roles, enhances students’ practical ability and job adaptability, and innovates the ideas and methods of talent cultivation mode in applied colleges and universities. The research not only provides specific practical guidance for applied colleges and universities in the digital transformation of education, but also provides new ideas and methods for the construction of a strong educational country. At the same time it provides new perspectives for the theoretical and practical development of the field, and contributes to the sustainable development of the field.