Artificial intelligence, sustainability and higher education: a systematic literature review toward sustainable higher education (SHE) framework

Purpose 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. Design/methodology/approach 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. Findings 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). Originality/value 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.

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Publication Details

Journal
International Journal of Educational Management
Published
2025-12-18
DOI
https://doi.org/10.1108/ijem-12-2024-0773
Primary Topic
Sustainability in Higher Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence, sustainability and higher education: a systematic literature review toward sustainable higher education (SHE) framework

International Journal of Educational Management
Sustainability in Higher Education
article

Artificial intelligence, sustainability and higher education: a systematic literature review toward sustainable higher education (SHE) framework

article en

Abstract

Purpose 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. Design/methodology/approach 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. Findings 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). Originality/value 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.

International Journal of Educational Management
Vienna University of Economics and Business (AT), University of Cambridge (GB), Cambridge School (PT), Bridge University (SS), National University (US)
Quality Education
Openalex Percentile: Top 20%
Sustainability in Higher Education
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