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Digital Leadership: Towards a Dynamic Managerial Capability Perspective of Artificial Intelligence-Driven Leader Capabilities

Sahadat Hossain et al.

Journal of Leadership and Organizational Studies2025https://doi.org/10.1177/15480518251319624article
ABDC A
Weight
0.70

Abstract

A new form of human-machine collaborative capabilities has been called to complement traditional capabilities to ensure higher but more responsible performance in artificial intelligence (AI)-driven organizational environments. Dynamic Managerial Capabilities (DMC) allow organizations to use their resources to neutralize threats and harness opportunities in competitive environments. Using DMC as our theoretical framework, we conducted 20 semi-structured interviews to explore the dimensions of leaders’ capabilities in AI environments with two specific aims. First, to identify the leaders’ essential capabilities in the AI environment and second, to develop a novel AI-driven digital leadership capability framework to lead AI-driven organizations effectively. Our findings show that leaders who dynamically manage AI tools and processes are better equipped to succeed in organizations where AI is a key factor. Our findings have theoretical implications for DMC theory and leadership as well as practical implications for effectively managing ethical issues of emerging technologies. We conclude by outlining research opportunities on how AI-driven leader capabilities can make digital leadership more effective.

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https://doi.org/https://doi.org/10.1177/15480518251319624

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@article{sahadat2025,
  title        = {{Digital Leadership: Towards a Dynamic Managerial Capability Perspective of Artificial Intelligence-Driven Leader Capabilities}},
  author       = {Sahadat Hossain et al.},
  journal      = {Journal of Leadership and Organizational Studies},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/15480518251319624},
}

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Evidence weight

0.70

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.82 × 0.4 = 0.33
M · momentum1.00 × 0.15 = 0.15
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.