Artificial Intelligence in Malaysian Higher Education: A Critical Review of Lecturers’ Challenges, Readiness and Pedagogical Transformation in Teaching and Learning

Abstract

The rapid advancement of Artificial Intelligence (AI), particularly generative AI technologies, has significantly transformed teaching and learning practices in higher education. While AI offers substantial opportunities to improve instructional efficiency, personalized learning, and assessment automation, its integration also introduces multidimensional challenges for lecturers. This study critically reviews global and Malaysian literature on the issues and challenges faced by lecturers in adapting AI technologies within higher education teaching and learning environments. A qualitative critical literature review approach was employed through systematic searching and thematic synthesis of scholarly publications indexed in academic databases between 2019 and 2026. The analysis identified five major themes affecting lecturers’ adaptation to AI: academic integrity and assessment transformation, pedagogical restructuring, AI literacy and competency gaps, ethical and privacy concerns, and institutional readiness. The findings indicate that although these challenges are globally prevalent, they are more pronounced within the Malaysian context due to uneven technological infrastructure, limited institutional policies, insufficient professional training, and varying levels of digital readiness among educators. Furthermore, the increasing dependence of students on generative AI tools raises concerns regarding critical thinking, authentic learning, and independent knowledge construction. This paper argues that AI integration should not be viewed merely as a technological issue but as a broader pedagogical and institutional transformation process. The study contributes to the growing discourse on AI in higher education by proposing an AI Adaptation Readiness Framework consisting of technological, pedagogical, ethical, and institutional dimensions. The framework provides a contextual reference for policymakers and higher education institutions in designing sustainable AI integration strategies. Ultimately, successful AI implementation requires a holistic and human-centered approach that balances technological innovation with educational integrity and pedagogical quality.