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

Bevilacqua, Simone ORCID: https://orcid.org/0009-0001-5303-9457, Masárová, Jana ORCID: https://orcid.org/0000-0001-9202-0735, Perotti, Francesco Antonio ORCID: https://orcid.org/0000-0002-4719-7774 and Ferraris, Alberto ORCID: https://orcid.org/0000-0003-3125-1710 (2025) Enhancing top managers' leadership with artificial intelligence : insights from a systematic literature review. Review of Managerial Science . DOI 10.1007/s11846-025-00836-7

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Official URL: https://doi.org/10.1007/s11846-025-00836-7


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.

Item Type:Article
Uncontrolled Keywords:Artificial intelligence; Top managers; Leadership; Upper echelons theory; Digital transformation
JEL classification:M12 - Personnel Management; Executives; Executive Compensation
O32 - Management of Technological Innovation and R&D
Divisions:Corvinus Institute for Advanced Studies (CIAS)
Subjects:Management, business policy, business strategy
Funders:Università degli Studi di Torino
Projects:Open access within the CRUI-CARE Agreement
DOI:10.1007/s11846-025-00836-7
ID Code:10874
Deposited By: MTMT SWORD
Deposited On:29 Jan 2025 15:23
Last Modified:29 Jan 2025 15:23

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