Relationship Between Artificial Intellegence and Leadership in Decision Making: A Bibliometric Analysis
DOI:
https://doi.org/10.30588/jmp.v15i1.2110Keywords:
Artificial Intelligence, AI, Strategic Decision-Making, Ethic, LeadershipAbstract
This study investigates the relationship between artificial intelligence (AI) and leadership in decision-making within the context of a rapidly evolving digital landscape. The integration of AI in leadership is a timely topic due to its transformative potential. This research examines the impact of AI on leadership and decision-making processes. Despite growing interest, limited research explores AI's implications for leadership using bibliometric approaches, particularly regarding ethical and social dimensions. A bibliometric analysis was performed on publications from 1982 to 2025, concentrating on countries with advanced technological infrastructure. Visualization tools such as VOSviewer are used to identify trends, key themes, and collaborative networks. The findings highlight significant contributions from the U.S., China, and the EU, with research emphasizing AI-driven decision-making, leadership styles, and predictive analytics. AI fosters collaborative, data-driven leadership, though gaps remain in understanding ethical challenges. AI significantly enhances leadership decision-making by enabling data-informed strategies and adaptive styles. Organizations must address ethical concerns and provide training to maximize AI's potential while ensuring responsible implementation.
References
Bláha, J., Klimsza, L., Lokaj, A., & Nierostek, L. (2021). Multidimensional analysis of ethical leadership for business development. European Journal of Sustainable Development, 10(1), 290–302. https://doi.org/10.14207/ejsd.2021.v10n1p290
Blumenthal, D. (2017). Data Withholding in the Age of Digital Health. Milbank Quarterly, 95(1), 15–18. https://doi.org/10.1111/1468-0009.12239
Cath, C., Wachter, S., Mittelstadt, B., Taddeo, M., & Floridi, L. (2018). Artificial Intelligence and the ‘Good Society’: the US, EU, and UK approach. Science and Engineering Ethics, 24(2), 505–528. https://doi.org/10.1007/s11948-017-9901-7
Glänzel, W., & Moed, H. F. (2002). State-of-the-Art Report Journal impact measures in bibliometric research. In Budapest Scientometrics (Vol. 53, Issue 2). Kluwer Academic Publishers.
Karakose, T., Demirkol, M., Yirci, R., Polat, H., Ozdemir, T. Y., & Tülübaş, T. (2023a). A Conversation with ChatGPT about Digital Leadership and Technology Integration: Comparative Analysis Based on Human–AI Collaboration. Administrative Sciences, 13(7). https://doi.org/10.3390/admsci13070157
Karakose, T., Demirkol, M., Yirci, R., Polat, H., Ozdemir, T. Y., & Tülübaş, T. (2023b). A Conversation with ChatGPT about Digital Leadership and Technology Integration: Comparative Analysis Based on Human–AI Collaboration. Administrative Sciences, 13(7). https://doi.org/10.3390/admsci13070157
Kar, S., Kar, A. K., & Gupta, M. P. (2021). Modeling Drivers and Barriers of Artificial Intelligence Adoption: Insights from a Strategic Management Perspective. Intelligent Systems in Accounting, Finance and Management, 28(4), 217–238. https://doi.org/10.1002/isaf.1503
Leung, X. Y., Sun, J., & Bai, B. (2017). Bibliometrics of social media research: A co-citation and co-word analysis. International Journal of Hospitality Management, 66, 35–45. https://doi.org/10.1016/j.ijhm.2017.06.012
Liu, Y. (2013). Sustainable competitive advantage in turbulent business environments. International Journal of Production Research, 51(10), 2821–2841. https://doi.org/10.1080/00207543.2012.720392
Losbichler, H., & Lehner, O. M. (2021). Limits of artificial intelligence in controlling and the ways forward: a call for future accounting research. Journal of Applied Accounting Research, 22(2), 365–382. https://doi.org/10.1108/JAAR-10-2020-0207
McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence.
Mong, D. D., & Thanh, H. P. (2024). Relationship between artificial intelligence and legal education: A bibliometric analysis. Knowledge and Performance Management, 8(2), 13–27. https://doi.org/10.21511/kpm.08(2).2024.02
Narin, F. (1987). Bibliometric techniques in the evaluation of research programs (Vol. 14).
Oosthuizen, J. H. (2024). Applying the Triarchic Theory of Cognitive Disposition in AI stewardship. South African Journal of Business Management, 55(1). https://doi.org/10.4102/sajbm.v55i1.4363
Pritchard, A. (1969). Statistical Bibliography or Bibliometrics? Journal of Documentation, 25, 348–349.
Qiu, J. P., Dong, K., & Yu, H. Q. (2014). Comparative study on structure and correlation among author co-occurrence networks in bibliometrics. Scientometrics, 101(2), 1345–1360. https://doi.org/10.1007/s11192-014-1315-6
Roy, A., Newman, A., Round, H., & Bhattacharya, S. (2024). Ethical Culture in Organizations: A Review and Agenda for Future Research. Business Ethics Quarterly, 34(1), 97–138. https://doi.org/10.1017/beq.2022.44
Silva, F. S. V., Schulz, P. A., & Noyons, E. C. M. (2019). Co-authorship networks and research impact in large research facilities: benchmarking internal reports and bibliometric databases. Scientometrics, 118(1), 93–108. https://doi.org/10.1007/s11192-018-2967-4
Tsai, C. Y., Marshall, J. D., Choudhury, A., Serban, A., Tsung-Yu Hou, Y. Y., Jung, M. F., Dionne, S. D., & Yammarino, F. J. (2022). Human-robot collaboration: A multilevel and integrated leadership framework. Leadership Quarterly, 33(1). https://doi.org/10.1016/j.leaqua.2021.101594
van Eck, N. J., & Waltman, L. (2017). Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics, 111(2), 1053–1070. https://doi.org/10.1007/s11192-017-2300-7
Wang, Y. (2021). Artificial intelligence in educational leadership: a symbiotic role of human-artificial intelligence decision-making. Journal of Educational Administration, 59(3), 256–270. https://doi.org/10.1108/JEA-10-2020-0216
Weber-Lewerenz, B., & Vasiliu-Feltes, I. (2022). Empowering Digital Innovation by Diverse Leadership in ICT – A Roadmap to a Better Value System in Computer Algorithms. Humanistic Management Journal, 7(1), 117–134. https://doi.org/10.1007/s41463-022-00123-7
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Mochammad Rifni Rachmat Prasetyo
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with Jurnal Maksipreneur agree to the following terms:
Authors retain copyright and grant the Jurnal Maksipreneur right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License that allows others to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material) the work for any purpose, even commercially with an acknowledgment of the work's authorship and initial publication in Jurnal Maksipreneur.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in Jurnal Maksipreneur. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
