Artificial Intelligence in Higher Education: A Scoping Review of Applications, Challenges, and Policy Directions
TL;DR
The review shows that AI offers substantial potential for personalised learning, scalable feedback, administrative automation and curriculum innovation, but that effective integration requires transparent governance, educator training, reliable evidence, accessibility and a commitment to ethical and human-centred use.
Abstract
This article presents a scoping review of the emerging transformative role of Artificial Intelligence (AI) in higher education. Using a Population-Concept-Context (PCC) review design, we focus on the implications of AI for three major stakeholder groups: students, educators and institutions. Based on academic studies and grey literature from 2010 onwards, the review covers AI technologies, including machine learning, natural language processing, intelligent tutoring systems, learning analytics, chatbots and generative AI, and examines their pedagogical, administrative and ethical impacts. We analyse stakeholder demand, teaching and learning innovations, AI literacy education, institutional implementation barriers, data privacy, algorithmic bias, academic integrity and policy governance. The review shows that AI offers substantial potential for personalised learning, scalable feedback, administrative automation and curriculum innovation, but that effective integration requires transparent governance, educator training, reliable evidence, accessibility and a commitment to ethical and human-centred use. The article concludes with best-practice and policy recommendations for responsible AI implementation and adoption in higher education.