Mapping the AI Surge in Higher Education: A Bibliometric Study Spanning a Decade (2015–2025)

There has recently been a pronounced global escalation in scholarly output concerning Artificial Intelligence (AI) within the context of higher education (HE). However, the precise locus of this growth remains ambiguous, thereby hindering the systematic integration of critical AI trends into HE practices. To address this opacity, the present study adopts a rigorous and impartial analytical approach by synthesizing datasets from the Web of Science (WoS) and Scopus through the Biblioshiny platform. In addition, independent examinations of WoS and Scopus data were conducted using co-occurrence network analyses in VOSviewer, which revealed comparable patterns of cluster strength across both datasets. Complementing these methods, Latent Dirichlet Allocation (LDA) was employed to extract and interpret thematic structures within locally cited references, thereby providing deeper insights into the extant research discourse. Findings revealed significant acceleration patterns from 2023 concerning publication trends, annual growth patterns, cited references, top authors, leading journals, and leading countries. Patterns of strengths from co-occurrence networks in VOSviewer revealed growing interest in generative AI tools, AI ethics, and concerns about AI integration into the curriculum in HE. The LDA analysis identified two dominant themes: the pedagogical integration of generative AI tools and broader academic discourse on AI ethics that correlated with the VOSviewer findings. This enhanced the credibility, reliability, and validity of the bibliometric techniques applied in the study. Recommendations and future directions offer valuable insights for policymakers and stakeholders to address pedagogical integration of generative AI tools in HE. The development of frameworks and ethical guidelines are important to address fair and transparent adoption of AI in HE. Further, global inequalities in adoption, aligning with UNESCO’s Sustainable Development Goals, are crucial to ensure equitable and responsible AI integration in HE.