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

M. Tabata,

Cris Wildermuth,

Kevin Bottomley

и другие.

Journal of Leadership Studies, Год журнала: 2025, Номер unknown

Опубликована: Март 14, 2025

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

Язык: Английский

Exploring consumer intentions to continue: Integrating task technology fit and social technology fit in generative AI based shopping platforms DOI
Debarun Chakraborty, Ciro Troise, Stefano Bresciani

и другие.

Technovation, Год журнала: 2025, Номер 142, С. 103189 - 103189

Опубликована: Фев. 12, 2025

Язык: Английский

Процитировано

1

Artificial Intelligence Technology, Organizational Learning Capability, and Corporate Innovation Performance: Evidence from Chinese Specialized, Refined, Unique, and Innovative Enterprises DOI Open Access

Shumei Han,

Di Zhang, Hongfeng Zhang

и другие.

Sustainability, Год журнала: 2025, Номер 17(6), С. 2510 - 2510

Опубликована: Март 12, 2025

In the context of global economic digital transformation and technological innovation, application AI Technology has a profound impact on corporate innovation development. Existing research primarily focused direct effect Corporate Innovation Performance, while there is limited exploration its interaction with organizational learning mechanisms. Based Dynamic Capabilities Theory, this study constructs framework “Technology—Individual Learning Capability—Team Capability—Innovation Performance”, analyzing how enhances capabilities to drive improvements in performance explores moderating role Organizational Capability. Through empirical analysis data from Specialized, Refined, Unique, Innovative Enterprises China, finds that significantly Capability playing critical role. Additionally, heterogeneity indicates factors such as production factors, industry characteristics, firm size influence effectiveness enhancing performance. This reveals pathway through which optimizes mechanisms improve performance, offering both theoretical support practical guidance for strategic decision-making.

Язык: Английский

Процитировано

0

Generative AI capabilities for green supply chain management improvement: extended dynamic capabilities view DOI
Taufik Kurrahman,

Feng Ming Tsai,

Ming K. Lim

и другие.

International Journal of Logistics Research and Applications, Год журнала: 2025, Номер unknown, С. 1 - 28

Опубликована: Март 17, 2025

Язык: Английский

Процитировано

0

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

M. Tabata,

Cris Wildermuth,

Kevin Bottomley

и другие.

Journal of Leadership Studies, Год журнала: 2025, Номер unknown

Опубликована: Март 14, 2025

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

Язык: Английский

Процитировано

0