Abstract: By empowering the internal governance of applied universities through data-driven operation, intelligent analysis and precise decision-making, artificial intelligence effectively improves governance efficiency and scientific decision-making capacity. It remodels the traditional bureaucratic governance model, promotes collaborative governance among multiple subjects, and expands the governance scope from traditional administrative management to the full coverage of teaching, scientific research and social services. Current intelligent governance practices still face practical dilemmas including technical deviation of governance goals, weakening of subject initiative, and algorithmic bias in governance content. Accordingly, establishing a humanistic and technological symbiosis mechanism, balancing data control and individual rights and interests, and integrating algorithmic advantages with governance wisdom can effectively address the difficulties of intelligent transformation, and further promote the in-depth integration of intelligent technology and educational governance in applied universities.