A Critical Analysis of Generative AI in Higher Education: Benefits, Challenges, and Future Directions

Abstract

With the rapid development of artificial intelligence (AI), generative artificial intelligence (GenAI) has been widely applied in higher education, specifically bringing both opportunities and potential challenges. This review focuses on the application of GenAI in teaching, learning, assessment and institutional governance within the higher education context. By adopting a literature review approach, this paper reviews and analyses research on GenAI in education. The findings reveal that GenAI can effectively improve teaching efficacy, enable personalised learning experiences, and streamline assessment procedures. However, its implementation also draws attention to concerns regarding academic integrity, data privacy, algorithmic bias, and ethical governance. In accordance, higher education institutions should strengthen AI literacy training for faculty and students, while improving institutional guidelines and establishing responsible governance mechanisms. Future research is recommended to conduct longitudinal investigations, cross-cultural comparative analyses, and in-depth studies on teacher professional development, in order to support the sustainable and long-term integration of GenAI into higher education.