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A Bibliometric Analysis to Study the Evolution of Artificial Intelligence in Business Ethics

Author

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  • Mario Tani
  • Valerio Muto
  • Gianpaolo Basile
  • Giulia Nevi

Abstract

The contemporary world is witnessing the pervasive diffusion of artificial intelligence (AI) across diverse societal domains. Concurrently, the implementation of these technologies in numerous management areas raises novel and critical ethical considerations. Considering that AI is not a neutral technology, this study employs a bibliometric approach to conduct a systematic literature review, aiming to understand the evolution of this nascent field within management studies. Our analysis is limited to publications from 2016 onward, a year widely recognized as marking the onset of significant AI dissemination. By examining the recent years of diffusion and the evolution of this phenomenon, our work reveals a fragmented field. To investigate thematic evolution, we used the Cobo method, partitioning the corpus into three distinct time slices with cut‐off points at 2020 and 2022. The findings indicate that, despite the emergence of key themes and a substantial body of research exploring AI from both technical and philosophical standpoints, the field remains in its initial stages of development. This analysis underscores the increasing relevance of research in management science concerning the responsible and ethical application of AI technologies. Consequently, this area presents considerable opportunities for future management research employing diverse managerial and theoretical frameworks, particularly in relation to the antecedents of ethical AI adoption and the implications of AI for ethical leadership.

Suggested Citation

  • Mario Tani & Valerio Muto & Gianpaolo Basile & Giulia Nevi, 2026. "A Bibliometric Analysis to Study the Evolution of Artificial Intelligence in Business Ethics," Business Ethics, the Environment & Responsibility, John Wiley & Sons, Ltd., vol. 35(2), pages 655-677, April.
    • Handle: RePEc:wly:buseth:v:35:y:2026:i:2:p:655-677
    DOI: 10.1111/beer.12797
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