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

K. D. Kadykov ()

Administrative Consulting, 2026, issue 3

Abstract: 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.

Date: 2026
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