Mapping responsible artificial intelligence in business and management: Trends, influence, and emerging research directions

Abstract

The rapid integration of AI into business and management demands ethical and responsible technology design and deployment. While various policies and frameworks exist, there is limited understanding of operationalizing responsible artificial intelligence (RAI). The literature remains fragmented, lacking cohesion and clarity. This bibliometric analysis quantitatively evaluates RAI literature’s research trends, key authors, collaborations, and thematic evolution in the business and management domain. A carefully designed search protocol based on an extensive literature review was used to retrieve 1942 research papers from the Scopus database (1981–2025), reflecting a 13.12 % annual growth rate and an average of 25.79 citations per paper. The study applied bibliographic coupling, keyword co-occurrence, and thematic mapping techniques using VOSviewer and Biblioshiny to identify intellectual structures and conceptual linkages. The results reveal four key clusters: "Ethics and Social Impacts of AI", "AI Adoption and Human-AI Interaction", "Auditing, Explainability, and Accountability in AI", and "Corporate Governance and Data Responsibility in AI". Future research directions for each cluster are proposed, providing valuable insights for practitioners and academicians. The paper highlights critical implications for developing responsible AI strategies in business and offers guidance for advancing scholarly work in this growing field.