Artificial Intelligence (AI) is rapidly reshaping the landscape of higher education; yet, a comprehensive mapping of scholarly trends, thematic evolution, and emerging research priorities remains limited. Addressing this gap, the present study conducts a bibliometric analysis of 9,905 journal articles sourced from the Scopus database using a rigorously curated search protocol. Analytical tools such as Biblioshiny (R package) and VOSviewer facilitated performance and network analysis. The findings reveal four thematic clusters: (1) AI-driven personalization and Pedagogical Innovation in Higher Education; (2) Pedagogical Transformation and Learner Interaction through AI; (3) AI, Academic Integrity, and Pedagogical Shift; and (4) Ethical Tech, Sustainability, and Consumer-Centric Business Innovation. The study provides research directions for each cluster following an examination of the overall application of AI in higher education institutions (HEIs). Bibliometric insights are enhanced and contextualized by a Focus Group Discussion (FGD) with academic experts and EdTech professionals. This qualitative element validates and extends bibliometric subjects, investigating the real-world hurdles, strategic opportunities, and ethical conflicts associated with the deployment of AI in higher education. The twin-method approach sheds light on how academic literature and institutional practice perceive, accept, and discuss AI. The study provides research directions for each cluster after surveying the overall application of AI in HEI. Contributing to the existing literature and policy dialog is a strategic knowledge map outlining probable applications of AI in academic settings from a business and management perspective. The study’s focus on business and management literature provides insights into organizational and strategic aspects of AI adoption while acknowledging the need for cross-disciplinary integration with technical and pedagogical research to develop comprehensive implementation frameworks.
Verma et al. (Thu,) studied this question.