Artificial Intelligence (AI) and The Future of Higher Education: A Systematic Literature Review of Adoption, Research, Ethics, and Teaching & Learning
TL;DR
The study concludes that AI should function as a supportive technology that complements human judgement rather than replacing academic responsibility, providing implications for universities, educators, researchers, students, and policymakers.
Abstract
Artificial Intelligence (AI), particularly Generative Artificial Intelligence (GenAI), is rapidly reshaping higher education by transforming academic research, teaching practices, learning processes, and institutional approaches to technology adoption. However, the rapid expansion of AI also raises concerns regarding academic integrity, privacy, data ownership, algorithmic bias, misinformation, and responsible use. This systematic literature review (SLR) synthesises recent evidence on the role of AI in higher education, with particular attention to four dimensions: AI adoption, AI-assisted academic research, AI ethics, and AI-enabled teaching and learning. Following the PRISMA framework, studies were identified through Scopus and Web of Science and assessed using predefined inclusion, exclusion, and quality appraisal criteria. From the initial 260 records, the screening and eligibility processes resulted in 20 studies being included in the final qualitative synthesis. The findings reveal that AI-assisted academic research represents the most prominent research area (35%), followed by AI-enabled teaching and learning (25%), AI adoption (20%), and AI ethics (20%). The reviewed studies demonstrate that AI supports literature reviews, academic writing, text revision, data analysis, referencing, personalised learning, feedback, student engagement, and research productivity. At the same time, effective implementation requires AI literacy, critical judgement, ethical awareness, institutional guidance, and appropriate training. The review identifies a significant need for integrated and longitudinal research examining AI adoption, ethical practice, learning outcomes, critical thinking, research quality, and student engagement across diverse disciplines and contexts. The study concludes that AI should function as a supportive technology that complements human judgement rather than replacing academic responsibility, providing implications for universities, educators, researchers, students, and policymakers.