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Journals / Uluslararası Yönetim İktisat ve İşletme Dergisi / 2026 / Cilt: 22 Sayı: 2

MAPPING THE INTERSECTION OF ARTIFICIAL INTELLIGENCE AND LEADERSHIP RESEARCH: A BIBLIOMETRIC ANALYSIS OF WOS PUBLICATIONS (2016–2024)

YAPAY ZEKA VE LİDERLİK ARAŞTIRMALARININ KESİŞİMİNİN HARİTALANMASI: WOS YAYINLARININ BİBLİYOMETRİK ANALİZİ (2016–2024)

Halil Hakdan Öz(BAYBURT ÜNİVERSİTESİ, REKTÖRLÜK)0000-0002-1970-6105
Fetullah Battal(BAYBURT ÜNİVERSİTESİ, İKTİSADİ VE İDARİ BİLİMLER FAKÜLTESİ)0000-0002-2895-0193
Pages
739–758
Publication Date
2026-06-27
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The study was carried out based on the data of various types of researches in the Web of Science database and conducted between 2016 and 2024

📌 3 Key Takeaways

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Objective & Hypothesis:In the Industry 4.0 era, where Artificial Intelligence (AI) technologies are becoming increasingly widespread, studies in the field of leadership are trying to unite the issues of AI and leadership under a common roof by emphasising the main perspectives of leadership.
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Key Findings & Data:In existing research, the interaction between AI and leadership is evaluated from three different perspectives.
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Conclusion & Impact:The study was carried out based on the data of various types of researches in the Web of Science database and conducted between 2016 and 2024
🔬Design:Araştırma Makalesi
📍Scope:2016 Verileri
⚙️Variables:Yapay Zeka · Liderlik · Bibliyometrik Analiz

Abstract

In the Industry 4.0 era, where Artificial Intelligence (AI) technologies are becoming increasingly widespread, studies in the field of leadership are trying to unite the issues of AI and leadership under a common roof by emphasising the main perspectives of leadership. In existing research, the interaction between AI and leadership is evaluated from three different perspectives. The first one is that AI will support leadership functions (development perspective). The second is that AI will replace leadership in the future (Replacement perspective). The third is that the influence of AI on leadership organisations is overestimated (sceptic perspective). In this study, systematic insights from multiple perspectives on the impact of AI technologies on leadership in today’s organisations has been attempted through bibliometric analysis. In this way, it is aimed to summarise the studies on AI and leadership, to identify the trends of research topics and to identify research gaps. Finally, the possible input of this study is to deliver a basis for future empirical and applied studies on related topics. The study was carried out based on the data of various types of researches in the Web of Science database and conducted between 2016 and 2024

Özet

Yapay zeka (YZ) teknolojilerinin giderek yaygınlaştığı Endüstri 4.0 döneminde, liderlik alanındaki çalışmalar liderliğin ana bakış açılarını vurgulayarak yapay zeka ve liderlik konularını ortak bir çatı altında birleştirmeye çalışmaktadır. Mevcut araştırmalarda YZ ve liderlik arasındaki etkileşim üç farklı bakış açısı ile değerlendirilmektedir. Bunlardan ilki YZ’nin liderlik işlevlerine destek olacağıdır. (Geliştirme perspektifi). İkincisi YZ’nin gelecekte liderliğin yerini alacağıdır. (Değiştirme perspektifi). Üçüncüsü YZ’nin liderlik ve örgütler üzerindeki etkisinin fazla abartıldığıdır. (Kuşkucu perspektif). Bu çalışmayla YZ tabanlı teknolojilerin modern örgütlerin liderlikleri üzerindeki etkisine yönelik olarak farklı bakış açıklarının bibliyometrik analiz aracılığıyla sistemli görüntüsü çıkartılmaya çalışılmıştır. Böylelikle YZ ve liderlik konularına yönelik olarak yapılan çalışmaların özeti, araştırma konularının eğilimleri, konu ile ilgili yayın yapan dergiler, araştırmacılar, ve araştırma boşluklarının belirlenmesi amaçlanmıştır. Nihayetinde bu çalışmanın olası katkısı ilgili konulara yönelik olarak gelecekteki ampirik ve uygulamalı çalışmalara temel oluşturmasıdır. Çalışma Web of Science veri tabanında yer alan ve 2016-2024 yılları arasında gerçekleştirilmiş farklı türdeki araştırmaların verileri baz alınarak gerçekleştirilmiştir.

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Cite This Article

Öz, H. H., Battal, F. (2026). MAPPING THE INTERSECTION OF ARTIFICIAL INTELLIGENCE AND LEADERSHIP RESEARCH: A BIBLIOMETRIC ANALYSIS OF WOS PUBLICATIONS (2016–2024). Uluslararası Yönetim İktisat ve İşletme Dergisi, Cilt: 22 Sayı: 2, 739–758. https://doi.org/10.17130/ijmeb.1688910

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References (47)

  1. Alblooshi, M. A. J. A., Mohamed, A. M., & Yusr, M. M. (2023). Moderating role of artificial intelligence between leadership skills and business continuity. International Journal of Professional Business Review, 8(6), e03225. https://doi.org/10.26668/businessreview/2023.v8i6.3225
  2. Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
  3. Arney, K. (2017). Algorithm’s gonna get you. The times educational supplement.
  4. Avolio, B. J., & Gardner, W. L. (2005). Authentic leadership development: Getting to the root of positive forms of leadership. The Leadership Quarterly, 16(3), 315–338. https://doi.org/10.1016/j.leaqua.2005.03.001
  5. Avolio, B. J., & Yammarino, F. J. (2013). Reflections, closing thoughts, and future directions. In B. J. Avolio & F. J. Yammarino (Eds.), Transformational and charismatic leadership: The road ahead (10th anniversary ed., pp. 449–470). Emerald Group Publishing Limited
  6. Bernardini, A., Sônego, A., & Pozzebon, E. (2018). Chatbots: An analysis of the state of art of literature. In workshop on advanced virtual environments and education, 1-6. https://doi.org/10.5753/wave.2018.1
  7. Bughin, J., & Hazan, E. (2017). The new spring of artificial intelligence: A few early economies. VoxEu.org 21.
  8. Caputo, A., & Kargina, M. (2021). A user-friendly method to merge Scopus and Web of Science data during bibliometric analysis. Journal of Marketing Analytics, 10(1), 82-88. https://doi.org/10.1057/s41270-021-00142-7
  9. De Cremer, D. (2019). Leading artificial ıntelligence at work: A matter of facilitating human‐algorithm cocreation. Journal of Leadership Studies, 13(1), 81-83. https://doi.org/10.1002/jls.21637
  10. Dhamija, P., Chiarini, A., & Shapla, S. (2021). Technology and leadership styles: a review of trends between 2003 and 2021. The TQM Journal, 35(1), 210-233. https://doi.org/10.1108/tqm-03-2021-0087
  11. Dirik, D., Eryılmaz, İ., & Erhan, T. (2023). Post-truth kavramı üzerine yapılan çalışmaların vosviewer ile bibliyometrik analizi. Sosyal Mucit Academic Review, 4(2), 164-188.
  12. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
  13. Erkutlu, H., Erdemir Ergün, E., Köseoğlu, İ., & Vurgun, T. (2023). Yapay zeka ve örgütsel davranış. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 13(3), 1403-1417. https://doi.org/10.30783/nevsosbilen.1246678
  14. Gezici, H. (2023). Kamu yönetiminde yapay zekâ: avrupa birliği. Uluslararasi Akademik Birikim Dergisi, 6(2). https://doi.org/10.53001/uluabd.2023.59
  15. Gil, D., Hobson, S., Mojsilović, A., Puri, R., & Smith, J. (2020). AI for management: An overview. The future of management in an AI world: Redefining purpose and strategy in the fourth industrial revolution, 3-19. https://doi.org/10.1007/978-3-030-20680-2_1
  16. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. Cambridge, MA: MIT Press. https://doi.org/10.7551/mitpress/10206.001.0001
  17. Herold, D. M., Fedor, D. B., Caldwell, S., & Liu, Y. (2008). The effects of transformational and change leadership on employees’ commitment to a change: A multilevel study. Journal of Applied Psychology, 93(2), 346–357. https://doi.org/10.1037/0021-9010.93.2.346
  18. Kambur, E. (2022). Yapay zeka çağında insan kaynakları yönetimi konusunda yazılmış türkçe makaleler üzerine bir araştırma. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 48, 139-152.
  19. Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15-25. https://doi.org/10.1016/j.bushor.2018.08.00
  20. Karamustafa, A., & Arsan, A. (2019). Gelecekte karar vericiler kim olacak? İnsan mı yapay zeka mı? In Internatıonal Congress of Management Economy and Policy 2019 Spring Proceedings Book.
  21. Kolbjørnsrud, V., Amico, R., & Thomas, R. (2017). Partnering with AI: how organizations can win over skeptical managers. Leadership, 45(1), 37-43. https://doi.org/10.1108/sl-12-2016-0085
  22. Kollmann, T., Kollmann, K., & Kollmann, N. (2023). Artificial leadership: Digital transformation as a leadership task between the chief digital officer and artificial intelligence. International Journal of Business Science and Applied Management, 18(1), 79–95. https://doi.org/10.69864/ijbsam.18-1.172
  23. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. https://doi.org/10.1038/nature14539
  24. Lichtenthaler, U. (2020). Extremes of acceptance: employee attitudes toward artificial intelligence. Journal of business strategy, 41(5), 39-45. https://doi.org/10.1108/jbs-12-2018-0204
  25. Loureiro, S., Guerreiro, J., & Tussyadiah, I. (2021). Artificial intelligence in business: State of the art and future research agenda. Journal of Business Research, 129, 911-926. https://doi.org/10.1016/j.jbusres.2020.11.001
  26. Malone, T. (2019). How can human-computer “superminds” develop business strategies? The Future of Management in an AI World, 165-183. https://doi.org/10.1007/978-3-030-20680-2_9
  27. Mariska, B., Prasetyo, Y., & Fadhilah, F. (2021). Perception and prospective analysis of artificial ıntelligence on human capital and its ımpact on human resources in the ındustrial revolution era 4.0. Enrichment: Journal of Management, 12(1), 146-151. https://doi.org/10.35335/enrichment.v12i1.172
  28. Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt.
  29. McCarthy, J. (1992). Reminiscences on the history of time-sharing. IEEE Annals of the History of Computing, 14(1), 19-24.
  30. Michael, k., & Miller, K. (2013). Big data: New opportunities and new challenges. Computer, 46(6), 22-24. https://doi.org/10.1109/mc.2013.196
  31. Moldenhauer, L., & Londt, C. (2019). Leadership, artificial intelligence and the need to redefine future skills development. Journal of Leadership, Accountability and Ethics, 16(1), 155-160. https://doi.org/10.33423/jlae.v16i1.1363
  32. Moral-Muñoz, J., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. El Profesional de La Información, 29(1). https://doi.org/10.3145/epi.2020.ene
  33. Muzaffar, A., Mahmood, H., Ramzan, M., Rizvi, S., & Rizvi, S. (2014). Impact of technology on performance of employees (a case study on Allied Bank Ltd, Pakistan). World Applied Sciences Journal, 29(2), 271-276. https://doiorg/10.5829/idosi.wasj.2014.29.02.1897
  34. Odugbesan, J. A., Aghazadeh, S., Al Qaralleh, R. E., & Sogeke, O. S. (2023). Green talent management and employees’ innovative work behavior: The roles of artificial intelligence and transformational leadership. Journal of Knowledge Management, 27(3), 696–716. https://doi.org/10.1108/JKM-08-2021-0601
  35. Oosthuizen, R. (2022). The fourth industrial revolution–smart technology, artificial intelligence, robotics and algorithms: Industrial psychologists in future workplaces. Frontiers in Artificial Intelligence, 5. https://doi.org/10.3389/frai.2022.913168
  36. Önder, M., & Saygılı, H. (2018). Yapay zekâ ve kamu yönetimine yansımaları. Türk İdare Dergisi, 487, 629-668.
  37. Pabuçcu, R., & İşcan Ö. F. (2025). Yapay Zekâ ve Liderlik: Dönüştürücü Liderlik Tarzının Çalışan Tutumlarına Etkisi. Uluslararası Ekonomi, İşletme ve Politika Dergisi, 9(1), 195-210. https://doi.org/10.29216/ueip.1607837
  38. Roig-Tierno, N., Gonzalez-Cruz, T., & Llopis-Martinez, J. (2017). An overview of qualitative comparative analysis: A bibliometric analysis. Journal of Innovation & Knowledge, 2(1), 15-23. https://doi.org/10.1016/j.jik.2016.12.002
  39. Sestino, A., & De Mauro, A. (2022). Leveraging artificial intelligence in business: Implications, applications and methods. Technology Analysis & Strategic Management, 34(1), 16-29. https://doi.org/10.1080/09537325.2021.1883583
  40. Sun, Z., Sandoval, L., Crystal-Ornelas, R., Mousavi, S., Wang, J., Lin, C., John, A. (2022). A review of earth artificial ıntelligence. Computers & Geosciences, 159. https://doi.org/10.1016/j.cageo.2022.105034
  41. Titareva, T. (2021, February). Leadership in an artificial ıntelligence era. In Leading Change Conference. James Madison University, (1-26) USA.
  42. Ünal, A., & Kılınç, İ. (2020). Yapay zekâ işletme yönetimi ilişkisi üzerine bir değerlendirme. Yönetim Bilişim Sistemleri Dergisi, 6(1), 51-78.
  43. Wang, O., & Ngai, E. (2020). Event study methodology in business research: A bibliometric analysis. Industrial Management & Data Systems, 120(10), 1863-1900. https://doi.org/10.1108/imds-12-2019-0671
  44. Wijayati, D., Rahman, Z., Fahrullah, A., Rahman, M., Arifah, I., & Kautsar, A. (2022). A study of artificial intelligence on employee performance and work engagement: the moderating role of change leadership. International Journal of Manpower, 43(2), 486-512. https://doi.org/10.1108/ijm-07-2021-0423
  45. World Economic Forum. (2015). Deep shift: technology tipping points and societal ımpact. Retrieved from https://www3.weforum.org/docs/WEF_GAC15_Technological_Tipping_Points_report_2015.pdf Accessed 10.09.2024.
  46. Yao, M., Zhou, A., & Jia, M. (2018). Applied artificial intelligence: A handbook for business leaders. Topbots Incorporated.
  47. Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007