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Enhancing top managers' leadership with artificial intelligence: insights from a systematic literature review

Author

Listed:
  • Simone Bevilacqua

    (University of Turin)

  • Jana Masárová

    (Alexander Dubcek University of Trenčin)

  • Francesco Antonio Perotti

    (University of Turin
    University of Agder)

  • Alberto Ferraris

    (University of Turin
    University of Nicosia
    Corvinus University of Budapest)

Abstract

In the contemporary landscape of digital transformation (DT), the wave of artificial intelligence (AI) is radically restructuring the managerial processes of organizations. As a result, the influence of top managers is emerging as a determining factor in the effectiveness of business strategies related to AI innovation. Academics have provided a large body of literature on this topic, drawing on upper echelons theory, which states that top managers' leadership influences companies' strategic decisions and performance. Leaders have revolutionized their roles and skills to exploit the full potential of AI and integrate it into the business decision-making process effectively. However, given the fragmented nature of existing studies, a systematic literature review is needed to consolidate and clarify how AI impacts top managers' leadership. This paper presents findings involving bibliometric and content analysis tools, examining 63 articles from 31 highly ranked academic journals. Three research clusters emerge: (1) AI-driven skills of top managers' leadership; (2) factors driving top managers' decision to adopt AI in organizations; and (3) the strategic use of AI. The article contributes to upper echelons theory, providing a holistic perspective on top managers' leadership in the AI era and a guidance framework for successfully integrating AI in businesses. Finally, the study offers scholars avenues for future research and provides practical insights for top managers seeking to harness AI technologies to enhance their strategic leadership in organizations.

Suggested Citation

  • Simone Bevilacqua & Jana Masárová & Francesco Antonio Perotti & Alberto Ferraris, 2025. "Enhancing top managers' leadership with artificial intelligence: insights from a systematic literature review," Review of Managerial Science, Springer, vol. 19(9), pages 2899-2935, September.
    • Handle: RePEc:spr:rvmgts:v:19:y:2025:i:9:d:10.1007_s11846-025-00836-7
    DOI: 10.1007/s11846-025-00836-7
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    JEL classification:

    • M12 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Personnel Management; Executives; Executive Compensation
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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