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All Journal The IC-BESTS (International Conference on Business, Economics, Technology, and Social Sciences)
Asep Candra Hidayat
Politeknik LP3I Jakarta

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HUMAN CENTERED ARTIFICIAL INTELLIGENCE IN UNIVERSITY MANAGEMENT: A SYSTEMATIC LITERATURE REVIEW Nika Sintesa; Yunita Indriany; Asep Candra Hidayat
IC-BESTS: International Conference on Business, Economics, Technology, and Social Sciences 2026: The IC-BESTS (International Conference on Business, Economics, Technology, and Social Sciences
Publisher : POLITEKNIK LP3I JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34127/icbests.v1i1.243

Abstract

This study aims to systematically review the literature on Human-Centered Artificial Intelligence (HCAI) in higher education management and develop a research framework that can guide future research and institutional practices. This study employed a Systematic Literature Review (SLR) approach following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Relevant articles published between 2018 and 2025 were retrieved from Scopus, Web of Science, and IEEE Xplore databases and screened based on predefined inclusion and exclusion criteria. The findings reveal that HCAI applications in higher education management mainly focus on six dimensions: administrative efficiency, strategic decision-making, student support services, learning analytics, governance and ethics, and stakeholder engagement. The review also identifies five critical enablers of successful HCAI implementation, namely digital leadership, AI literacy, ethical governance, organizational readiness, and collaborative culture.This study offers an integrated conceptual framework that synthesizes fragmented research on HCAI and explains the relationships among contextual factors, HCAI enablers, human-AI interaction processes, and institutional outcomes. The proposed framework provides practical guidance for university leaders and policymakers in designing responsible and human-centered AI strategies. Furthermore, this study contributes to the literature by establishing a comprehensive foundation for future empirical research and advancing understanding of sustainable AI implementation in higher education management.
Co-Authors sintesa, nika Yunita Indriany