Same Technology, Different Problems? A Comparative Bibliometric Analysis of Generative AI Across Education, Business, Communication, and Governance

Abstract

The rapid diffusion of generative artificial intelligence (GenAI) has raised questions about whether this technological phenomenon is problematised differently across institutional domains. This study compares GenAI scholarship in education, business and organisational research, communication and media and public governance, law, and policy. Four domain-specific Web of Science Core Collection corpora for 2023–2026 comprised 6,132, 1,901, 300 and 444 documents, respectively. Bibliometric performance analysis, thematic mapping, and author-keyword co-occurrence analysis were conducted using Bibliometrix/Biblioshiny and VOSviewer. Distinct thematic configurations emerged across the four domains. Education foregrounds learning, assessment, AI literacy, and academic integrity. Business research emphasises innovation, technology adoption, decision making, and organisational capability. Communication scholarship centres on journalism, trust, disinformation, and informational credibility, whereas research on governance foregrounds regulation, accountability, rights, and legal responsibility. These patterns are not treated as direct measures of institutional logics. Instead, the study develops a theory-informed mapping that relates empirical thematic configurations to institutional problems and normative priorities. GenAI is not problematised uniformly; its institutional salience is shaped by divergent criteria of legitimate knowledge, organisational value, professional authority, and public accountability. The study offers a comparative framework for examining GenAI as an institutionally situated sociotechnical phenomenon while maintaining a clear distinction between bibliometric evidence and institutional interpretation.