The Future of Leadership in the Context of Artificial Intelligence and Automation: Navigating Ethical and Operational Challenges

Ebuka Emmanuel Aniebonam
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Ebuka Emmanuel Aniebonam: North Star Mutual School of Business, Department of Business, Innovation and Strategy, Southwest Minnesota State University Marshall Minnesota, USA

British Journal of Business and Psychology Research, 2025, vol. 1, issue 1, 52-62

Abstract: The integration of artificial intelligence (AI) and automation is reshaping leadership paradigms, presenting unprecedented opportunities and complex challenges for modern organizations. This paper explores the transformative impact of AI on leadership, emphasizing the ethical, strategic, and operational considerations that arise as technology becomes a cornerstone of decision-making and organizational processes. While AI enhances efficiency, adaptability, and innovation, it also raises concerns about data privacy, algorithmic bias, and job displacement. The paper delves into the dual mandate for leaders to leverage AI while addressing these ethical dilemmas, highlighting the blurred boundaries between management and leadership in AIdriven environments. Methodologically, the study employs multi-level analyses and mixed methods approaches to examine leadership traits, team dynamics, and organizational practices in the context of AI. Additionally, the paper underscores the potential of AI-driven tools, such as machine learning and virtual reality, to revolutionize leadership development by providing real-time feedback and scenario-based training. Recommendations emphasize the need for AI ethics training, inclusive leadership practices, and a human-centric approach to AI integration. By fostering transparency, equity, and interdisciplinary collaboration, leaders can harness AI's transformative potential while ensuring ethical responsibility. This study contributes to the evolving discourse on leadership in the digital era, offering insights for scholars and practitioners navigating the complexities of AI and automation.

Keywords: AI integration; leadership paradigms; strategic decision-making; data privacy; algorithmic bias (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:ris:bjobpr:022006

DOI: 10.47297/ppibjbpr2025010104

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