Artificial intelligence in higher education: a PRISMA 2020 review

Purpose Artificial Intelligence (AI) is making significant inroads in higher education (HE) institutions, revolutionizing how students learn and instructors teach. With the ability to analyze vast amounts of data quickly, AI can personalize learning experiences for students based on their individual needs and learning styles. The review aims to synthesize the literature regarding opportunities, challenges and current trends of AI in HE. Design/methodology/approach The fragmented body of knowledge in AI and its adoption in HE was aggregated by conducting this PRISMA 2020 review during 2014–2024, using the Scopus database as a source for literature. Findings The research findings of 33 primary reviews relevant to the research of AI in HE mapped the main opportunities, challenges and recent trends of AI in HE during this period. Personalized learning, automated feedback and grading, enhanced accessibility and better resource allocation are features of AI opportunities, while infrastructure and internet access, HR skills and ethical concerns about data privacy and security and integrity were the most challenges of AI in HE. Results indicate the exponential increase during the last four years in AI research that reflects the huge changes and development in all aspects of education. Research limitations/implications This review has some limitations regarding the data selection and analysis. Although PRISMA 2020 guidelines were applied, inclusion and exclusion criteria included many prior kinds of research that were not in HE. Social implications The implications for higher education functions are to advocate for AI responsibility that addresses social and ethical concerns that have the potential to undermine the effective integration of AI and its opportunities and challenges. Future research should conduct empirical studies on AI and HE and its assessment and evaluation in this context. Originality/value The review advances the literature by providing the current state of AI in HE, its applications and trends, opportunities and challenges and a research agenda for future works.