Bibliometric analysis of artificial intelligence in higher education based on the WoS database

Abstract

Abstract This study employs a bibliometric analysis to map the global research landscape of artificial intelligence (AI) in higher education, utilizing data from the Web of Science database. The results reveal a rapidly evolving field characterized by a tripartite integration of technology, management, and ethics. Research has progressed through distinct phases: foundational technological exploration (2016–2018), organizational integration and application (2019–2022), and current emphasis on generative AI and ethical governance (2023–2025). Geographically, the field is dominated by contributions from China, the United States, and England, with emerging participation from institutions in India, Macau, and Hong Kong. Influential journals such as MIS Quarterly and Harvard Business Review underpin the interdisciplinary knowledge base, bridging management science, information systems, and educational technology. While the study highlights growing collaboration networks and thematic diversification, it also identifies imbalances in research representation and practical implementation challenges. Future efforts should prioritize mixed-methods approaches, cross-disciplinary collaboration, and ethical frameworks to ensure AI’s equitable and effective integration into higher education systems. This research provides a comprehensive foundation for scholars, policymakers, and educators navigating the AI-driven transformation of higher education.