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Features and Barriers of AI Maturity Assessment (Case Study of the Federal Executive Authorities of the Russian Federation)

https://doi.org/10.55959/MSU2070-1381-113-2025-31-44

Abstract

This paper describes the practical implementation of measuring the AI maturity index using the example of federal executive authorities of the Russian Federation. The key barriers to the practical implementation of the assessment are identified, as well as the methods used by the author to solve them. During the testing of the methodology, three enlarged groups of barriers were identified using the example of the public sector: organizational and communication, methodological, and technical. It is important to note that the recommendations formulated in the article aimed at overcoming the identified barriers are universal and can be adapted to assess the digital maturity of organizations in any field. The experience of the analysis helps employees conduct such measurements to anticipate barriers in advance and take advantage of appropriate solutions. This approach ensures transparency, accuracy and scalability of the procedure, which is important for organizations of any type in the context of digital transformation. Also, aspects of this work can be used in the development of public policy in the field of AI implementation, as well as in the formation of recommendations for increasing the digital maturity of government authorities.

About the Author

E. S. Kharitonova
Higher School of Public Administration, Russian Presidential Academy of National Economy and Public Administration
Russian Federation

Ekaterina S. Kharitonova Researcher

Moscow



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Review

For citations:


Kharitonova E.S. Features and Barriers of AI Maturity Assessment (Case Study of the Federal Executive Authorities of the Russian Federation). Public Administration. E-journal (Russia). 2025;(113):31-44. (In Russ.) https://doi.org/10.55959/MSU2070-1381-113-2025-31-44

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ISSN 2070-1381 (Online)