Artificial Intelligence (AI) in Higher Education: Prospects, Challenges and Future Directions

This volume offers research-led synthesis of contemporary scholarship on AI in higher education, bringing together curated literature reviews, empirical studies, and policy-oriented analyses from a global perspective. Structured across six thematic parts, the book examines the evolution of AI in higher education, institutional policies and governance frameworks, AI-supported teaching and learning resources, the changing roles of teachers and learners and the ethical, legal, and equity-related implications of AI deployment. Chapters address generative AI, large language models, chatbots, learning analytics, robotic process automation, extended reality, gamification, and algorithmically mediated assessment, alongside critical discussions of disability inclusion, special education, bias mitigation, academic integrity, and copyright law. It highlights how AI is being interpreted, adopted, and contested across disciplines and regions. It serves as a reliable reference for  understanding the current state of the field and for informing future research, institutional decision-making, and responsible AI integration in higher education. The auto-summaries have been generated by a recursive clustering algorithm via the Dimensions Auto-summarizer by Digital Science handled by Subject Matter Experts and the editor(s) of this book. The editor(s) of this book selected which SN content should be auto-summarized and decided its order of appearance. Please be aware that these are abstractive auto-summaries, which consist of original sentences, but are not representative of its original paper, since we do not show the full length of the publication. Please note that only published SN content is represented here, and that curated books are still at an experimental stage.