Artificial intelligence (AI) has emerged as a transformative force in advancing Sustainable Development Goals (SDGs) and redefining higher education. Recently, AI has garnered significant attention from academia and industry due to its potential to address SDGs and shape the future of higher education. The prime objective of this study is to critically investigate the intersection of AI, sustainability and higher education (SHE) on the existing literature. The study also aims to develop a conceptual framework toward AI driven SHE.
This study is a systematic literature review employing Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, which is based on the Scopus and web of science databases based on the time frame of 2015–2024 in the context of higher education. Following the PRISMA guidelines, a systematic review was performed, yielding 39 pertinent articles for inclusion in the analysis. Descriptive analysis, thematic analysis, cluster analysis was conducted by VOS viewer software to reach reasonable conclusion on this intersection.
After conducting the review analysis, the findings reveal that three key themes have emerged in AI driven higher education such as customized learning experiences (first theme), accessibility (second theme) and optimizing resources allocation (third theme). Additionally, the study has created two categories to show the challenge in implementing AI in higher education: pedagogical challenges (category one), and policy and governance challenges (category two).
Finally, this study proposes and develops a SHE conceptual framework based on AI. To fully harness the potential benefits of AI technology towards achieving SHE, universities and policymakers should pay more attention to ethical aspects of AI implications and adoption in learning content.
