Artificial Intelligence and the Evolution of Management Learning: Insights from Emerging Research

Although the growing use of AI in management education has drawn attention from scholars, the field of study remains fragmented and lacks a common understanding of its conceptual underpinnings. To close this gap, this study employs bibliometric analysis to methodically examine the evolution, major figures, subject areas, and cooperative patterns of academic discourse on artificial intelligence in management education. Using the PRISMA 2020 criteria, this study employs a bibliometric analytic technique based on recognized scientific mapping procedures (Donthu et al., 2021; Van Eck & Waltman, 2017) (Page et al., 2021). Biblioshiny (a web interface of Bibliometrix in R) was used to perform descriptive statistics, performance analysis, trend detection, network visualization of co-authorship, co-citation, and keyword co-occurrence. The results provide a comprehensive analysis of the academic field of artificial intelligence in management education, highlighting both established and emerging areas. "Generative AI and Large Language Models," "Human-AI Collaborative Paradigm," and "Strategic Digital Transformation in Education" are the emerging research fields highlighted by the study's thematic clusters based on word co-occurrence.