Using Project-Oriented Approach and Artificial Intelligence in Public Administration: Goals, Objectives and Risks

Goal. The study aims to comprehensively analyze the goals, objectives, and risks of integrating a project-oriented approach and artificial intelligence (AI) technologies into the public administration system of the Russian Federation. In the context of the transition to a data-driven public administration model and the implementation of large-scale national projects, there is a need to transform traditional bureaucratic procedures into flexible, adaptive mechanisms.

Methods. The methodological basis of the work was a systematic approach, which allowed considering the integration of AI and project management as a single evolutionary process. A content analysis of strategic documents of the Russian Federation (including the updated National Strategy for the Development of AI until 2030) and EU regulations was carried out. The method of comparative analysis was used to compare domestic and foreign practices of implementing intelligent decision support systems in the public sector.

Results. The study identified and systematized key areas of project management transformation: automation of routine operations, predictive risk analytics, and intelligent decision support. An author's definition of "intelligent project management in the public sector" is proposed, along with a system of performance indicators. Based on empirical data, the effectiveness of AI integration in public administration is confirmed. A classification of risks has been developed, including technological, legal, ethical, and personnel aspects.

Conclusions. It is concluded that the successful integration of AI into project management is possible only with the creation of a specialized regulatory environment that enshrines the "human-in-the-loop" principle. The integration of AI is shown to have systemic advantages over alternative approaches. A set of measures to minimize risks is proposed, including the development of national data infrastructure, the introduction of Explainable Artificial Intelligence standards, and the implementation of digital literacy programs for civil servants.

1. Brycheev A. S. Application of artificial intelligence in public authorities: challenges, issues and prospects // Bulletin of Eurasian Science [Vestnik Evraziiskoi nauki]. 2024. Vol. 16, N S6. URL: https://esj.today/11favn624.html. (In Russ.). EDN FCWPSM

2. Vasilenko L. A., Zotov V. V. Digitalization of public administration in Russia: risks, cases, problems // Digital Sociology [Tsifrovaya sotsiologiya]. 2020. Vol. 3, N 2. P. 4–16. (In Russ.). DOI 10.26425/2658-347X-2020-2-4-16; EDN DUXMRV

3. Voskanyan N. M., Korobitsina E. S. Implementation of artificial intelligence in project management: practices and challenges // Economics and Law. Current State and Development Prospects. Petrozavodsk, 2024. P. 143–150. (In Russ.). EDN JJMLQO

4. Guseva M. N., Brikoshina I. S., Glebanov A. I. Prospects for the use of artificial intelligence in project management // Economics and Entrepreneurship [Ekonomika i predprinimatel’stvo]. 2024. N 1 (162). P. 1002–1007. (In Russ.). DOI: 10.34925/EIP.2024.162.1.193; EDN TZSLCS

5. Dzgoev V. D., Tsutsiev M. A. Artificial intelligence in public administration // Budget [Byudzhet]. 2025. N 2. URL: https://bujet.ru/article/498593.php. (In Russ.). EDN ZDKHCE

6. Dobrolyubova E. I. Assessment of digital maturity of public administration // Information Society [Informatsionnoe obshchestvo]. 2021. N 2. P. 37–52. (In Russ.). DOI: 10.52605/16059921_2021_02_37; EDN ZSEGML

7. Iyupova L. K. Project management based on artificial intelligence: a global revolution // Innovation and Investment [Innovatsii i investitsii]. 2023. N 11. P. 119–122. (In Russ.). EDN OSAQYK

8. Kabanova E. E. Artificial intelligence in public administration: key problems and application prospects // Russian Journal of Management. 2025. Vol. 13, N 2. P. 1–14. (In Russ.). DOI: 10.29039/2500-1469-2025-13-2-1-14; EDN THNZKD

9. Musaeva A. Artificial intelligence in project management: opportunities and challenges // Journal of Monetary Economics and Management. 2024. N 9. P. 324–328. (In Russ.). DOI 10.26118/2782-4586.2024.50.45.066; EDN KDGQEX

10. Saidov Sh. R. The impact of artificial intelligence on the economy // Current Issues of Modern Economics [Aktual’nye voprosy sovremennoi ekonomiki]. 2023. N 3. P. 636–644. (In Russ.).

11. Styrin E. M. Government as a platform: approaches to implementation // Public Administration. E-journal [Gosudarstvennoe upravlenie. Elektronnyi vestnik]. 2022. N 90. P. 169–185. (In Russ.). DOI 10.24412/2070-1381-2022-90-169-185

12. Styrin E. M., Dmitrieva N. E. Digital transformation in public administration. Moscow: HSE Publishing House, 2023. 245 p. (In Russ.).

13. Fedotova M. A. Artificial intelligence technologies in predicting the effectiveness of teamwork // Research Result. Sociology and Management [Nauchnyi rezul’tat. Sotsiologiya i upravlenie]. 2019. Vol. 5, N 2. P. 93–106. (In Russ.). DOI 10.18413/2408-9338-2019-5-2-0-9; EDN DPDUZQ

14. Brynjolfsson E., McAfee A. The Second Machine Age. New York: W. W. Norton, 2014. 336 p.

15. Cate F. H. Government Data Mining // Harvard Civil Rights-Civil Liberties Law Review. 2008. Vol. 43, N 2. P. 435–489.

16. European AI Act: Regulation (EU) 2024/1689 // Official Journal of the European Union. 2024. URL: https://eur-lex.europa.eu/eli/reg/2024/1689/oj

17. Margetts H., Dunleavy P. The Second Wave of Digital-Era Governance // Philosophical Transactions of the Royal Society A. 2013. Vol. 371. DOI 10.1098/rsta.2012.0382

18. OECD. Artificial Intelligence in Society. Paris: OECD Publishing, 2019. DOI 10.1787/eedfee77-en.

19. O’Neil C. Weapons of Math Destruction. New York: Crown, 2016. 272 p.

20. Ratti C. et al. Mobile Landscapes // Environment and Planning B. 2006. Vol. 33, N 5. P. 727–748.

21. Sun T. Q., Medaglia R. Mapping the Challenges of AI in Public Sector // Government Information Quarterly. 2019. Vol. 36, N 2. DOI 10.1016/j.giq.2018.09.008

22. Valle-Cruz D. et al. A Review of AI in Government // ACM Digital Government. 2020. Vol. 1, N 4. P. 91–99. DOI 10.1145/3404140

23. Wirtz B. W., Weyerer J. C., Geyer C. AI and the Public Sector // International Journal of Public Administration. 2019. Vol. 42, № 7. P. 596–615. DOI 10.1080/01900692.2018.1498103

24. Zuiderwijk A. et al. Implications of AI in Public Governance // Government Information Quarterly. 2021. Vol. 38. Article 101577. DOI 10.1016/j.giq.2021.101577; EDN VENVHZ