Pandey, Varun (2025) Leadership in the AI Era: Navigating and shaping the future of organizational guidance. International Journal of Science and Research Archive, 15 (3). pp. 1737-1747. ISSN 2582-8185
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Abstract
The advent of Artificial Intelligence (AI) has catalyzed a significant transformation in organizational leadership paradigms. Traditional leadership theories, although foundational, must evolve to address the challenges and opportunities presented by AI integration. This paper critically examines how leadership roles and competencies are reshaped by AI, emphasizing four key dimensions: ethical leadership, adaptive agility, human-AI collaboration, and data-driven decision-making. Ethical leadership underscores the imperative for fairness, transparency, and accountability amidst algorithmic decision-making. Adaptive agility highlights the necessity for leaders to foster continuous learning and organizational flexibility, exemplified by successful digital transformations. The exploration of human-AI collaboration discusses managing hybrid teams, redefining roles, and building trust between human and artificial team members. Additionally, the integration of AI into decision-making processes accentuates the importance of balancing data-driven insights with strategic vision and human judgment. This synthesis indicates a paradigm shift towards augmented leadership, wherein leaders effectively merge technological prowess with enduring human values. The paper concludes with actionable recommendations for practitioners, educators, and policymakers and identifies areas for future research, thereby guiding leaders to harness AI responsibly and innovatively for organizational and societal benefit.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/ijsra.2025.15.3.1875 |
Uncontrolled Keywords: | AI-Driven Leadership; Ethical Artificial Intelligence; Adaptive Leadership; Human-AI Collaboration; Data-Driven Decision-Making; Digital Transformation Strategy |
Depositing User: | Editor IJSRA |
Date Deposited: | 27 Jul 2025 16:13 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/2623 |