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

被引:0
|
作者
Tabata, Mary [1 ]
Wildermuth, Cris [2 ]
Bottomley, Kevin [3 ]
Jenkins, Daniel [4 ]
机构
[1] Eastern Univ, Coll Business & Leadership, St Davids, PA 19087 USA
[2] Barry Univ, MS Leadership & Innovat, Miami, FL USA
[3] Indiana Inst Technol, Coll Business, Doctoral Programs, Ft Wayne, IN USA
[4] Univ Southern Maine, Leadership & Org Studies, Portland, ME USA
关键词
COMPLEXITY LEADERSHIP;
D O I
10.1002/jls.70005
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Mobile Generative AI: Opportunities and Challenges
    Zhang, Ye
    Zhang, Jinrui
    Yue, Sheng
    Lu, Wei
    Ren, Ju
    Shen, Xuemin
    IEEE WIRELESS COMMUNICATIONS, 2024, 31 (04) : 58 - 64
  • [2] Generative AI for Visualization: Opportunities and Challenges
    Basole, Rahul C.
    Major, Timothy
    IEEE COMPUTER GRAPHICS AND APPLICATIONS, 2024, 44 (02) : 55 - 64
  • [3] Integration of Big Data and AI in Educational Leadership Practices: Opportunities and Challenges
    Meng, Nian
    EURASIAN JOURNAL OF EDUCATIONAL RESEARCH, 2024, (111): : 47 - 67
  • [4] Generative AI in banking: empirical insights on integration, challenges and opportunities in a regulated industry
    Moharrak, Moayad
    Mogaji, Emmanuel
    INTERNATIONAL JOURNAL OF BANK MARKETING, 2025, 43 (04) : 871 - 896
  • [5] Opportunities and challenges of diffusion models for generative AI
    Chen, Minshuo
    Mei, Song
    Fan, Jianqing
    Wang, Mengdi
    NATIONAL SCIENCE REVIEW, 2024, 11 (12)
  • [6] Opportunities and challenges of diffusion models for generative AI
    Minshuo Chen
    Song Mei
    Jianqing Fan
    Mengdi Wang
    National Science Review, 2024, 11 (12) : 254 - 276
  • [7] Generative AI Meets Responsible AI: Practical Challenges and Opportunities
    Kenthapadi, Krishnaram
    Lakkaraju, Himabindu
    Rajani, Nazneen
    PROCEEDINGS OF THE 29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, KDD 2023, 2023, : 5805 - 5806
  • [8] Generative AI in Medicine and Healthcare: Promises, Opportunities and Challenges
    Zhang, Peng
    Kamel Boulos, Maged N.
    FUTURE INTERNET, 2023, 15 (09)
  • [9] Software Testing of Generative AI Systems: Challenges and Opportunities
    Aleti, Aldeida
    2023 IEEE/ACM INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: FUTURE OF SOFTWARE ENGINEERING, ICSE-FOSE, 2023, : 4 - 14
  • [10] The Paradox of Artificial Creativity: Challenges and Opportunities of Generative AI Artistry
    Garcia, Manuel B.
    CREATIVITY RESEARCH JOURNAL, 2024,