Mapping Artificial Intelligence Research in Business and Management Higher Education: A Bibliometric Analysis


  •  Kanjana Chumsong    
  •  Pattariya Wahamongkhon    
  •  Sorachai Sukpun    

Abstract

Artificial intelligence (AI) is reshaping business and management higher education, yet the field remains dispersed across educational, managerial, and technological conversations. This study maps that literature through a reproducible bibliometric review of Dimensions.ai records published from 2017 to 2025. The search and final export were completed on August 22, 2026. PRISMA 2020-guided screening retained 352 English-language open-access articles, chapters, and monographs. Descriptive indicators were combined with VOSviewer 1.6.20 analyses of co-authorship, contributor citations, cited-author co-citation, and title-and-abstract term co-occurrence.

Annual output increased from 1 publication in 2017 to 191 in the complete 2025 publication year. Citation impact was concentrated in a small number of recent studies, while the co-authorship network remained fragmented into several small groups. Country results placed the United Kingdom first among records with affiliation metadata, although country information was missing for 182 of 352 records. After removing metadata artifacts, the most frequent title-and-abstract terms included intelligence, ChatGPT, business, opportunity, assessment, and engagement. The study contributes a transparent, multi-layer map of an emerging field and identifies priorities for curriculum design, assessment, responsible AI governance, and stronger cross-institutional collaboration.



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