Artificial Intelligence in Higher Education: A Thematic Integrative Review of Applications, Users, Ethics, and Institutional Consequences
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The rapid diffusion of artificial intelligence (AI) across higher education has intensified debates regarding its pedagogical value, ethical implications, and institutional governance. Although a growing body of research documents specific AI-driven applications, less attention has been paid to who uses AI in higher education, for what purposes, under what ethical conditions, and with what institutional consequences. This study adopts a thematic integrative literature review to synthesise peer-reviewed research and policy literature on AI use in higher education published between 2011 and 2025. Guided by six analytical questions, the review examines key actors, dominant AI platforms and applications, purposes of use, ethical practices, existing ethical guidelines, and persistent research gaps across teaching and learning, assessment, research, administration, and student support. The findings reveal uneven and stratified patterns of AI adoption, with students and academic staff emerging as the dominant users, growing reliance on generative AI tools, fragmented ethical governance, and limited institutional readiness. Building on these insights, the study advances a conceptual framework that conceptualises AI use in higher education as a socio-technical process shaped by institutional actors, ethical principles, and governance mechanisms. The review concludes by identifying critical gaps in empirical evidence, ethical implementation, and Global South-focused research, and outlines implications for future scholarship, policy, and institutional practice.
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