Purpose. The purpose of the study is to determine the relationship between artificial intelligence and emotional intelligence in public administration and to justify the concept of digital leadership, which integrates technological solutions with the socio-emotional competencies of civil servants. The study explores how the balanced implementation of AI and EI contributes to improving decision-making quality, adaptability to changes, and effective leadership in public governance.
Design / methodology / approach. The study employs a systematic analysis to identify the structural connections between AI, EI, and leadership in public administration. A comparative analysis is applied to assess existing models of digital governance, while modeling is used to develop an integrated concept of digital leadership. This methodological approach enables the identification of key challenges associated with AI adoption, including algorithmic bias, the digital competence gap among public officials, and trust issues regarding automated decision-making.
Findings. The study establishes that the effective interaction between AI and EI in public administration is feasible only when leaders possess a combination of cognitive, emotional, and technological competencies. It is demonstrated that excessive automation without consideration of social aspects reduces public trust in government institutions and creates barriers in leader-subordinate communication. The research proposes a digital leadership model that harmonizes strategic thinking, adaptive personnel management, and AI-driven decision support. This model ensures that AI enhances governance efficiency without undermining the role of human expertise and social responsibility.
Practical implications. The study provides practical recommendations for improving leadership strategies in public administration, focusing on the development of digital competencies among civil servants, increasing the transparency of algorithmic decision-making, and implementing ethical oversight mechanisms for AI use. The findings contribute to the enhancement of governance strategies that balance technological advancements with human-oriented leadership principles.
Originality / value. The research is significant in the context of ongoing digital transformation in public administration. It emphasizes the necessity of integrating AI into decision-making processes while preserving the role of EI in leadership effectiveness. The proposed model of digital leadership offers a novel approach to optimizing governance structures, ensuring their adaptability, and maintaining trust in public institutions amid rapid technological advancements.
Future research directions. Further studies should focus on expanding AI capabilities for personalized leadership training, evaluating the effectiveness of emotional intelligence analysis in personnel policy, and developing regulatory frameworks to govern AI's influence on public administration processes.
1. Parkhomenko-Kutsevil, O. (2024). Obgruntuvannia vykorystannia tekhnolohii shtuchnoho intelektu u systemi upravlinnia personalom publichnoi sluzhby Ukrainy [Justification for the use of artificial intelligence technologies in the personnel management system of Ukraine’s public service]. Publichne upravlinnia: kontseptsii, paradyhma, rozvytok, udoskonalennia – Public Administration: Concepts, Paradigm, Development, Improvement, 8, 98–106. DOI: 10.31470/ 27866246- 2024-8-98-106 (in Ukrainian).
2. Prudius, O. (2023). Stratehichni napriamy tsyfrovoho rozvytku ekosystemy upravlinnia liudskymy resursamy derzhavnoi sluzhby Ukrainy v umovakh hlobalizatsii [Strategic directions of digital development in the human resources management ecosystem of Ukraine’s civil service in the context of globalization]. Aspekty publichnoho upravlinnia – Aspects of Public Administration, 11(1), 5–11. DOI: 10.15421/152301 (in Ukrainian).
3. Kraus, K. M., Kraus, N. M., & Holubka, S. M. (2022). Stanovlennia pratsi 4.0 v umovakh tsyfrovizatsii ta zastosunku shtuchnoho intelektu [Formation of Labor 4.0 in the conditions of digitalization and the application of artificial intelligence]. Yevropeiskyi naukovyi zhurnal ekonomichnykh ta finansovykh innovatsii – European Scientific Journal of Economic and Financial Innovations, 2(10), 19–31. Retrieved from https://elibrary.kubg.edu.ua/id/eprint/41864/ (in Ukrainian).
4. Nesterenko, H. P., & Boiko, V. V. (2024). Vykorystannia ShI pry pryiniatti rishen u publichnomu upravlinni ta vidpovidalnist za nykh [The use of AI in decision-making in public administration and responsibility for it]. Vcheni zapysky TNU imeni V. I. Vernadskoho. Seriia: Publichne upravlinnia ta administruvannia – Scientific Notes of Vernadsky TNU. Series: Public Administration and Governance, 35(6), 54–59. Retrieved from https://www.pubadm.vernadskyjournals.in.ua/journals/2024/6_2024/6_2024.p... (in Ukrainian).
5. Wirtz, B. W., Weyer, J. C., & Geyer, C. (2019). Artificial intelligence and the public sector – applications and challenges. International Journal of Public Administration, 42(7), 596–615. DOI: 10.1080/01900692.2018.1498103 (in English).
6. Criado, J. I., & Gil-Garcia, J. R. (2019). Creating public value through smart technologies and strategies: From digital services to artificial intelligence and beyond. International Journal of Public Sector Management, 32(5), 438–450. DOI: 10.1108/ijpsm-07-2019-0178 (in English).
7. Bhardwaj, B., Sharma, D., & Dhiman, M. C. (2023). AI and emotional intelligence for modern business management. IGI Global. Retrieved from https://books.google.com.ua/books?hl=uk&lr=&id=wVfgEAAAQBAJ&oi=fnd&pg=PR... (in English).
8. Kambur, E. (2021). Emotional intelligence or artificial intelligence?: Emotional artificial intelligence. Florya Chronicles of Political Economy, 7(2), 147–168. Retrieved from https://dergipark.org.tr/tr/pub/fcpe/issue/66453/982671 (in English).
9. Dudau, A., & Brunetto, Y. (2020). Debate: Managing emotional labour in the public sector. Public Money & Management, 40(1), 11–13. DOI: 10.1080/09540962.2019.1665912 (in English).
10. Isakova, Z. (2024). Ethical synergy: Integrating artificial intelligence in civil service project management for new governance. Iqtisodiyot va talim, 25(1), 16–22. Retrieved from https://cedr.tsue.uz/index.php/journal/article/view/1412 (in English).
11. Rokhsaritalemi, S., Sadeghi-Niaraki, A., & Choi, S.-M. (2023). Exploring emotion analysis using artificial intelligence, geospatial information systems, and extended reality for urban services. IEEE Access, 11, 92478–92495.DOI: 10.1109/ACCESS.2023.3307639 (in English).
12. Hrushchynska, N. M., & Mykhalchenko, O. A. (2021). Evrystyka tendentsii upravlinnia u suchasnykh svitovykh protsesakh [Heuristic trends in management in modern global processes]. Naukovyi pohliad: ekonomika ta upravlinnia –Scientific View: Economics and Management, 1(71), 17–22. DOI: 10.32836/2521-666X/2021-71-3 (in Ukrainian).
13. Vesolovska, M., & Shved, L. (2024). Strategizing soft skills resilience: A holistic approach to mitigating COVID-19 pandemic impact on workforce development. Qubahan Academic Journal, 4(2), 153–169. DOI: 10.48161/qaj.v4n2a193 (in English).
14. Goleman, D. (2001). Emotional intelligence: Issues in paradigm building. The emotionally intelligent workplace, 13(26). Retrieved from https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=0b62033fd... 895267f0c6c (date of access: 07.03.2025) (in English).
15. Mayer, J. D. (2002). MSCEIT: Mayer-Salovey-Caruso emotional intelligence test. Toronto, Canada: Multi-Health Systems. Retrieved from https://mikegosling.com/pdf/MSCEITDescription.pdf (date of access: 07.03.2025) (in English).
16. IBM Watson (2025). IBM Watson. Retrieved from https://www.ibm.com/watson
17. Google AI (2025). Google AI. Retrieved from https://ai.google
18. SAP SuccessFactors (2025). SAP SuccessFactors. Retrieved from https://www.sap.com/products/human-resources-hcm/successfactors.html
19. Workday AI (2025). Workday AI. Retrieved from https://www.workday.com
20. Palantir Gotham (2025). Palantir Technologies. Retrieved from https://www.palantir.com
21. Microsoft Azure AI (2025). Microsoft Azure AI. Retrieved from https://azure.microsoft.com/en-us/products/cognitive-services
22. Salesforce Einstein AI (2025). Salesforce Einstein AI. Retrieved from https://www.salesforce.com/products/einstein-ai
23. Chatbots AI by OpenAI (2025). OpenAI Chatbots AI. Retrieved from https://openai.com
24. COMPAS AI (2025). COMPAS Risk Assessment. Retrieved from https://www.equivant.com/compas-risk-needs-assessment