Generative AI Integration in Leadership Practice: Foundations, Challenges, and Opportunities

M. Tabata et al.

Journal of Leadership Studies2025https://doi.org/10.1002/jls.70005article
AJG 1
Weight
0.58

What the paper says

Integrating generative artificial intelligence (GenAI) into leadership practice represents a pivotal transformation in organizational dynamics, presenting unprecedented opportunities and complex challenges. The current article develops a comprehensive conceptual framework grounded in sociotechnical systems and complex adaptive leadership theories to guide future research and practice. By carefully examining leader‐follower relationships, decision‐making processes, and organizational learning patterns, we demonstrate how GenAI reshapes traditional leadership paradigms while raising critical ethical considerations. Our analysis reveals four key areas demanding attention: ethical decision‐making in AI implementation, trust dynamics between human and artificial agents, GenAI literacy development across organizational levels, and integrating AI systems with existing organizational structures and governance policies. The framework emphasizes the crucial balance between technological advancement and human‐centered leadership, particularly highlighting how the Human Interaction lens can guide responsible AI adoption. By identifying specific research questions in each domain, the article provides a roadmap for scholars and practitioners navigating the evolving landscape of AI‐enhanced leadership.

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https://doi.org/https://doi.org/10.1002/jls.70005

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@article{m.2025,
  title        = {{Generative AI Integration in Leadership Practice: Foundations, Challenges, and Opportunities}},
  author       = {M. Tabata et al.},
  journal      = {Journal of Leadership Studies},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1002/jls.70005},
}

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Evidence weight

0.58

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

F · citation impact0.58 × 0.4 = 0.23
M · momentum0.80 × 0.15 = 0.12
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.