As the application of artificial intelligence (AI) in higher education becomes increasingly widespread, it has emerged as a key focus of educational innovation and academic research. AI technologies are being rapidly integrated into various aspects of university education, transforming how knowledge is delivered, accessed, and assessed. This paper focuses on the application of AI in higher education, examining three main areas: the integration of AI in teaching and learning, the challenges that arise in the process, and strategic recommendations for effective implementation. Specifically, it analyzes how AI reshapes teaching models, curriculum development, the role of educators, and student learning behaviors. It also addresses concerns related to ethics, data privacy, equity, and teacher-student dynamics. Based on current research and case studies, the paper argues that AI holds significant potential in creating a more personalized, intelligent, and inclusive higher education ecosystem. Ultimately, AI is positioned not only as a tool but as a transformative force driving the future of educational reform.
Yibin Wang (2025) studied this question.