Optimization of management processes in central government bodies through the integration of artificial intelligence

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.318018

Keywords:

artificial intelligence, innovation, public administration, cyber security, transparency of management, efficiency of management processes

Abstract

The primary object of analysis in this study is the impact of artificial intelligence (AI) on various departments of a district state administration. The problem addressed by the research was to evaluate the key benefits and challenges of using AI to optimize management processes. The results demonstrated a significant increase in the efficiency of handling citizen inquiries, reducing the processing time from seven days to two days, indicating the high productivity of the implemented systems.

These results can be explained by the application of automating routine tasks and optimizing workflows, which lead to the rapid processing of inquiries and reduction of administrative burdens. Moreover, the increased internal consistency of the data, confirmed by Cronbach's alpha, indicates the reliability of the metrics and assessment tools used.

The distinctive features of the results, such as high transparency and efficiency of processes, became possible through the integration of the latest AI technologies, which helped solve the identified problem. These features allow AI to serve as an important tool in public administration reform.

The scope of practical application of the results includes the use of AI to enhance the quality of public services and optimize internal processes in public administration. Owing to the implementation of best practices in data management and cybersecurity, departments can achieve better interaction and efficiency, promoting the development of a transparent and effective management system.

The practical application of the proposed innovations could significantly improve the quality of interaction with citizens, ensuring greater satisfaction with services and compliance with modern efficiency requirements

Author Biographies

Alla Bashuk, Taras Shevchenko National University of Kyiv

Doctor of Social Communication, Associate Professor

Department of Advertising and Public Relations

Oleh Chechel, Open International University of Human Development "Ukraine"

Doctor of Science in Public Administration, Associate Professor

Department of Management and Administration

References

  1. Palmi, P., Corallo, A., Prete, M. I., Harris, P. (2020). Balancing exploration and exploitation in public management: Proposal for an organizational model. Journal of Public Affairs, 21 (3). https://doi.org/10.1002/pa.2245
  2. Kinder, T., Stenvall, J., Koskimies, E., Webb, H., Janenova, S. (2023). Local public services and the ethical deployment of artificial intelligence. Government Information Quarterly, 40 (4), 101865. https://doi.org/10.1016/j.giq.2023.101865
  3. Binhammad, M., Alqaydi, S., Othman, A., Abuljadayel, L. H. (2024). The Role of AI in Cyber Security: Safeguarding Digital Identity. Journal of Information Security, 15 (02), 245–278. https://doi.org/10.4236/jis.2024.152015
  4. Lee, J. W. (2020). Big Data Strategies for Government, Society and Policy-Making. The Journal of Asian Finance, Economics and Business, 7 (7), 475–487. https://doi.org/10.13106/jafeb.2020.vol7.no7.475
  5. Martinez, R. (2019). Artificial Intelligence: Distinguishing between Types & Definitions. Nevada Law Journal, 19 (3), 1015–1042. Available at: https://scholars.law.unlv.edu/nlj/vol19/iss3/9/
  6. van Noordt, C., Misuraca, G. (2022). Artificial intelligence for the public sector: results of landscaping the use of AI in government across the European Union. Government Information Quarterly, 39 (3), 101714. https://doi.org/10.1016/j.giq.2022.101714
  7. Zhang, B., Anderljung, M., Kahn, L., Dreksler, N., Horowitz, M. C., Dafoe, A. (2021). Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers. Journal of Artificial Intelligence Research, 71. https://doi.org/10.1613/jair.1.12895
  8. Mohapatra, S., Kumar, A. (2019). Developing a Framework for Adopting Artificial Intelligence. International Journal of Computer Theory and Engineering, 11 (2), 19–22. https://doi.org/10.7763/ijcte.2019.v11.1234
  9. Wirtz, B. W., Weyerer, J. C., Kehl, I. (2022). Governance of artificial intelligence: A risk and guideline-based integrative framework. Government Information Quarterly, 39 (4), 101685. https://doi.org/10.1016/j.giq.2022.101685
  10. Agba, M., Agba, G., Obeten, A. (2023). Artificial Intelligence and Public Management and Governance in Developed and Developing Market Economies. Journal of Public Administration, Policy and Governance Research (JPAPGR), 1(2), 1–14. Available at: https://jpapgr.com/index.php/research/article/view/13
  11. Patel, H., Guttula, S., Mittal, R. S., Manwani, N., Berti-Equille, L., Manatkar, A. (2022). Advances in Exploratory Data Analysis, Visualisation and Quality for Data Centric AI Systems. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 4814–4815. https://doi.org/10.1145/3534678.3542604
  12. Rodgers, W., Nguyen, T. (2022). Advertising Benefits from Ethical Artificial Intelligence Algorithmic Purchase Decision Pathways. Journal of Business Ethics, 178 (4), 1043–1061. https://doi.org/10.1007/s10551-022-05048-7
  13. Reddy, S., Allan, S., Coghlan, S., Cooper, P. (2019). A governance model for the application of AI in health care. Journal of the American Medical Informatics Association, 27 (3), 491–497. https://doi.org/10.1093/jamia/ocz192
  14. Ortiz-Ospina, E. Beltekian, D., Roser, M. (2018). Trade and Globalization. Our World in Data. Available at: https://ourworldindata.org/trade-and-globalization
  15. Mishra, A. K., Tyagi, A. K., Dananjayan, S., Rajavat, A., Rawat, H., Rawat, A. (2024). Revolutionizing Government Operations. Conversational Artificial Intelligence, 607–634. https://doi.org/10.1002/9781394200801.ch34
  16. Petrovskyy, P., Isachenko, D. (2021). The role of artificial intelligence in the provision of government services. Electronic Scientific Publication “Public Administration and National Security,” 4 (45). https://doi.org/10.25313/2617-572x-2024-4-9819
  17. Ospina, S. M., Esteve, M., Lee, S. (2017). Assessing Qualitative Studies in Public Administration Research. Public Administration Review, 78 (4), 593–605. https://doi.org/10.1111/puar.12837
  18. Alon-Barkat, S., Busuioc, M. (2022). Human–AI Interactions in Public Sector Decision Making: “Automation Bias” and “Selective Adherence” to Algorithmic Advice. Journal of Public Administration Research and Theory, 33 (1), 153–169. https://doi.org/10.1093/jopart/muac007
  19. Smith, A., Anderson, J. (2014). AI, Robotics, and the Future of Jobs. Pew Research Center. Available at: https://www.pewresearch.org/internet/2014/08/06/future-of-jobs/
  20. Agarwal, P. K. (2018). Public Administration Challenges in the World of AI and Bots. Public Administration Review, 78 (6), 917–921. https://doi.org/10.1111/puar.12979
  21. Zhang, W., Zuo, N., He, W., Li, S., Yu, L. (2021). Factors influencing the use of artificial intelligence in government: Evidence from China. Technology in Society, 66, 101675. https://doi.org/10.1016/j.techsoc.2021.101675
  22. Kumar, N., Singh, M., Upreti, K., Mohan, D. (2021). Blockchain Adoption Intention in Higher Education: Role of Trust, Perceived Security and Privacy in Technology Adoption Model. Proceedings of International Conference on Emerging Technologies and Intelligent Systems, 303–313. https://doi.org/10.1007/978-3-030-82616-1_27
  23. Girinskienė, V. (2024). Artificial intelligence in the public sector: progress versus regress? Applied Scientific Research, 3 (1), 64–82. https://doi.org/10.56131/tmt.2024.3.1.213
  24. Hjaltalin, I. T., Sigurdarson, H. T. (2024). The strategic use of AI in the public sector: A public values analysis of national AI strategies. Government Information Quarterly, 41 (1), 101914. https://doi.org/10.1016/j.giq.2024.101914
  25. Coursey, D., Norris, D. F. (2008). Models of E‐Government: Are They Correct? An Empirical Assessment. Public Administration Review, 68 (3), 523–536. https://doi.org/10.1111/j.1540-6210.2008.00888.x
  26. Alhosani, K., Alhashmi, S. M. (2024). Opportunities, challenges, and benefits of AI innovation in government services: a review. Discover Artificial Intelligence, 4 (1). https://doi.org/10.1007/s44163-024-00111-w
  27. Janssen, M., Kuk, G. (2016). The challenges and limits of big data algorithms in technocratic governance. Government Information Quarterly, 33 (3), 371–377. https://doi.org/10.1016/j.giq.2016.08.011
  28. Mökander, J., Schroeder, R. (2024). Artificial Intelligence, Rationalization, and the Limits of Control in the Public Sector: The Case of Tax Policy Optimization. Social Science Computer Review. https://doi.org/10.1177/08944393241235175
Optimization of management processes in central government bodies through the integration of artificial intelligence

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Published

2024-12-27

How to Cite

Bashuk, A., & Chechel, O. (2024). Optimization of management processes in central government bodies through the integration of artificial intelligence. Eastern-European Journal of Enterprise Technologies, 6(13 (132), 98–105. https://doi.org/10.15587/1729-4061.2024.318018

Issue

Vol. 6 No. 13 (132) (2024): Transfer of technologies: industry, energy, nanotechnology

Section

Transfer of technologies: industry, energy, nanotechnology

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Copyright (c) 2024 Alla Bashuk, Oleh Chechel

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