Artificial intelligence in higher education: a systematic review of contributions to SDG 4 (quality education) and SDG 10 (reduced inequality)

Abstract

Purpose This research systematically examines how AI technologies in higher education contribute to achieving Sustainable Development Goals (SDGs), focusing on SDG 4 (quality education) and SDG 10 (reduced inequalities). Design/methodology/approach We included peer-reviewed articles published in English between 2015 and 2025, identified through ERIC, Web of Science, Education Source Ultimate, Sustainability Reference Center and Academic Search Ultimate databases. Out of the 1,673 records, 1,360 were screened after 313 duplicates were removed. We conducted full-text reviews on 75 eligible articles and 51 met the inclusion criteria. Findings The findings indicate that AI advances quality education through personalized learning, predictive analytics and adaptive systems, while promoting reduced inequalities via accessibility and inclusive support for underrepresented groups. Key challenges include ethical concerns, infrastructure gaps and cultural resistance. Research limitations/implications This review is limited by its focus on English-language, peer-reviewed articles published between 2015 and 2025, potentially excluding relevant studies in other languages and publication types. Practical implications Our review highlights the need for equitable AI implementation in HEIs by promoting ethical frameworks, infrastructure investment and educator training to maximize its potential for advancing SDGs. Originality/value This study is the first to have a broad view of the application of AI in higher education institutions (HEIs) in the effort of achieving SDGs 4 and 10. It reveals the scope, patterns and implications of AI use and synthesizes barriers impacting its integration and their influence on fulfilling SDG 4 and SDG 10 objectives.

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