Empirical Insights into AI-Augmented Leadership: A Multi-Industry Comparative Study
The application of AI as one of the industry 4.0 drivers has drastically changed leadership roles in various industries. This paper gives a practical and comparative assessment of how AI has influenced Leadership within the financial, health, Manufacturing and education sectors. The study also examines how AI supports decision-making and automates leadership activities and challenges in human-centred positions. These unit evaluations critique the uses of AI in different sectors through qualitative and quantitative data collection to show that it is both an enabler and a disruptor. We discuss how this approach raises significant ethical issues, including Bias, responsibility, and privacy, that remain barriers to the expanded use of AI in Leadership. Moreover, this paper outlines the blended skills required within leaders to perform in AI-scaffolded environments, including data sense, emotional intelligence, and ethical reasoning. Reflectively, the discussion explores an element of autonomy in accomplishing AI’s functionality and leadership values, leaning on oversights and integrative approaches. Through the identified research gaps, met by real world data findings in the context of this paper, practical recommendations and implications for managing organizations interested in embracing AI while preserving critical human leadership attributes are presented. It is only after realizing and stating that AI is not at all a substitution for human leaders but a solid resource to be introduced to strengthen Leadership and handhold leaders in different fields.
Authors
- Jayeeta Debnath Munshi (ORCID: https://orcid.org/0009-0003-4800-8415)
Institutions
- National Institute of Technology Agartala (IN)
- Tripura University (IN)
Publication Details
- Journal
- International Journal of Engineering and Information Management
- Published
- 2025-01-15
- DOI
- https://doi.org/10.52756/ijeim.2025.v01.i01.004
- Citations
- 2
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 2.48