ECONOMIC AND MANAGERIAL EFFECTS OF USING ARTIFICIAL INTELLIGENCE IN THE RUSSIAN PUBLIC SECTOR

This article provides a comprehensive analysis of the economic and managerial effects of implementing artificial intelligence technologies in state and municipal government bodies of the Russian Federation. The empirical basis of the study is the results of the All-Russian Monitoring of Intellectual Maturity, which covered over two thousand regional executive bodies from 89 constituent entities of the Russian Federation, approximately 750 local government bodies, and nineteen priority areas of activity. The integrated intellectual maturity index of regional government bodies was found to be 3.9 points out of a possible 100, with only 2.2% of regional executive bodies using artificial intelligence technologies. Economic and managerial benefits were found to be concentrated primarily in leading regions and industries with developed digital infrastructure, while most regions limited themselves to pilot projects due to systemic resource shortages [6]. Critical barriers include low availability of computing power, platform solutions, data, and specialized personnel. Artificial intelligence was demonstrated to be primarily implemented in support processes, while core administrative and managerial functions were less involved. The need to prioritize five areas of state support was substantiated: funding infrastructure solutions, institutionalizing data management, developing human resource competencies, creating systems for evaluating and replicating successful practices, and strengthening trust and security mechanisms. The study's results provide a methodological basis for developing targeted management solutions for digital transformation in the public sector.

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Publication Details

Journal
Russian Journal of Management
Published
2025-11-15
DOI
https://doi.org/10.29039/2500-1469-2025-13-10-241-252
Primary Topic
Digital Economy and Transformation
Type
article
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article

ECONOMIC AND MANAGERIAL EFFECTS OF USING ARTIFICIAL INTELLIGENCE IN THE RUSSIAN PUBLIC SECTOR

Sergey Muzalev
Russian Journal of Management
Digital Economy and Transformation
article

ECONOMIC AND MANAGERIAL EFFECTS OF USING ARTIFICIAL INTELLIGENCE IN THE RUSSIAN PUBLIC SECTOR

Sergey Muzalev
article en

Abstract

This article provides a comprehensive analysis of the economic and managerial effects of implementing artificial intelligence technologies in state and municipal government bodies of the Russian Federation. The empirical basis of the study is the results of the All-Russian Monitoring of Intellectual Maturity, which covered over two thousand regional executive bodies from 89 constituent entities of the Russian Federation, approximately 750 local government bodies, and nineteen priority areas of activity. The integrated intellectual maturity index of regional government bodies was found to be 3.9 points out of a possible 100, with only 2.2% of regional executive bodies using artificial intelligence technologies. Economic and managerial benefits were found to be concentrated primarily in leading regions and industries with developed digital infrastructure, while most regions limited themselves to pilot projects due to systemic resource shortages [6]. Critical barriers include low availability of computing power, platform solutions, data, and specialized personnel. Artificial intelligence was demonstrated to be primarily implemented in support processes, while core administrative and managerial functions were less involved. The need to prioritize five areas of state support was substantiated: funding infrastructure solutions, institutionalizing data management, developing human resource competencies, creating systems for evaluating and replicating successful practices, and strengthening trust and security mechanisms. The study's results provide a methodological basis for developing targeted management solutions for digital transformation in the public sector.

Russian Journal of ManagementVol. 13(10)
Financial University (RU)
Openalex Percentile: Top 50%
Digital Economy and Transformation
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