Generative AI for Learning Individualization and Student Support in Sustainable Higher Education: A Systematic Review of Creative Agency, Equitable Learning, and Implications for SDG 4 and SDG 10

Generative AI (GenAI) promises individualized support in higher education, yet sustained learning and equity benefits remain uncertain. This systematic review examined learning individualization, student support, creative agency, equitable learning, and implications for Sustainable Development Goals (SDGs) 4 and 10. Prospectively registered (INPLASY202660012) and reported following PRISMA 2020, it searched Scopus, ERIC, ScienceDirect, and the MDPI Journals Platform. Sixty-one studies represented by 63 reports underwent independent dual appraisal using the Mixed Methods Appraisal Tool (criterion-level Cohen’s κ = 0.664) and narrative synthesis. Learner-directed individualization appeared in 46 studies; five documented system-driven adaptation. Creative-agency findings were mixed in 41 of 60 studies, combining ideation and autonomy with overreliance concerns. Equitable-learning findings were mixed in 17 of 35 studies, with accessibility and linguistic support alongside unequal access and benefit. Evidence frequently relied on self-reports, with limited long-term follow-up. Seven studies explicitly framed findings around SDG 4, one around SDG 10, and none measured official SDG indicators. Core themes remained represented after 39 studies were temporarily omitted in sensitivity analysis, without establishing robustness. GenAI offers flexible support, but sustained learning gains and reduced educational inequality remain unestablished. Future research should assess learning, compare groups longitudinally, and specify SDG targets.