Analysis of the use of artificial intelligence in economic sectors and the system of regional executive power of the Russian Federation


Cite item

Full Text

Abstract

Announced as part of the Presidential Address to the Federal Assembly in February 2024, the Data Economy national project defines the demand for artificial intelligence (AI) technology in the system of public administration, economic sectors and business activities. AI technology is increasingly penetrating business activities, production processes, and the system of public administration, creating the need to improve methods for assessing its impact on economic development. The goal of the work is to supplement the methodological tools for assessing the level of use of AI in the economy of the Russian Federation. The object of the study is the use of AI in certain sectors of the economy and regions. The subject of the study is the interrelation between the balanced income of economic sectors, regions of the Russian Federation and indicators of the use of AI in entrepreneurship and public administration practice. The work considers AI not as a separate branch of the economy, but as a technology that, in turn, has an impact on the development of individual industries and regions. The author identified a direct dependence of the positive financial results of the activities of individual sectors of the economy, regions and the use of AI technology in them. The study shows that regions and industries with a relatively more favorable financial position use AI more actively. On the one hand, this creates opportunities for the development of industries and regions; on the other hand, it creates a lag in the application of AI technology. The obtained result is applicable in the system of state planning, determining priorities for economic development of both individual industries and the economy as a whole.

 

About the authors

Evgeny Pavlovich Eroshenko

Ural Federal University named after the first President of Russia B.N. Yeltsin

Author for correspondence.
Email: evgeny.eroshenko@urfu.ru
ORCID iD: 0000-0002-4373-8414

PhD (Economics), assistant professor at the Institute of Economics and Management

Russian Federation, 620002, Russia, Yekaterinburg, Mira Street, 19

References

  1. McCarthy J. Programs with common sense. Proceedings of the Teddington Conference on the Mechanization of Thought Processes. London, 1959. 15 p. URL: http://jmc.stanford.edu/articles/mcc59/mcc59.pdf.
  2. Rodgers W. Artificial Intelligence in a Throughput Model: Some Major Algorithms. Boca Raton, CRC Press Publ., 2020. 47 p. doi: 10.1201/9780429266065.
  3. Bokhorov K.Yu. Algorithmic apophenia and aestheticization of data. Art & Culture Studies, 2021, no. 3, pp. 242–255. doi: 10.51678/2226-0072-2021-3-242-255.
  4. Adamenko A.A., Khorolskaya T.E., Podobnaya E.A. Classification of small businesses. Natural-Humanitarian Studies, 2018, no. 3, pp. 6–12. EDN: OTOMIQ.
  5. Daneykin Yu.V. Regional ecosystem of technological entrepreneurship: model and methodology for assessing performance (the case of the Novgorod region). Vestnik of Saint Petersburg University. Management, 2023, vol. 2, no. 3, pp. 337–365. doi: 10.21638/11701/spbu08.2023.304.
  6. Gurvich E.T., Krasnopeeva N.A. Determinants of public spending composition in the Russian regions. Voprosy ekonomiki, 2024, no. 1, pp. 5–32. doi: 10.32609/0042-8736-2024-1-5-32.
  7. Amelina E.A. Small and medium business: a place in the Russian economy and analysis of the current state. Kaluzhskiy ekonomicheskiy vestnik, 2019, no. 4, pp. 43–47. EDN: VNBQYK.
  8. Kuzmin V.N. Small and medium businesses as a tool to implement the state economic function. Vestnik Yuridicheskogo instituta MIIT, 2020, no. 1, pp. 107–117. EDN: EGMFAG.
  9. Shubin M.A., Antokhin Yu.N. Statistical analysis of government impact on the development of innovation activities. Ekonomika. Pravo. Innovatsii, 2021, no. 3, pp. 63–72. doi: 10.17586/2713-1874-2021-3-63-72.
  10. Gorodnova N.V. Application of artificial intelligence in the business sphere: current state and prospects. Voprosy innovatsionnoy ekonomiki, 2021, vol. 11, no. 4, pp. 1473–1492. doi: 10.18334/vinec.11.4.112249.
  11. Khusanov U.A., Kudratillaev M.B., Siddikov B.N., Dovletova S.B. Artificial intelligence in medicine. Science and Education, 2023, vol. 4, no. 5, pp. 773–782.
  12. Iskoskov M.O., Mitrofanova Ya.S. Development of tools to support the enterprise digital transformation project management system based on big data. Digital Economy & Innovations, 2024, no. 1, pp. 19–27. doi: 10.18323/2221-5689-2024-1-19-27.
  13. Butenko E.D. Artificial intelligence in banks today: experience and perspectives. Digest Finance, 2020, vol. 25, no. 2, pp. 230–242. doi: 10.24891/df.25.2.230.
  14. Baranov D.N. The potential of using digital technologies in the organization of social and labor relations in the field of housing and communal services. Bulletin of Moscow Witte University. Series 1: Economics and Management, 2023, no. 1, pp. 91–98. doi: 10.21777/2587-554X-2023-1-91-98.
  15. Massel L.V. Modern stage of artificial intelligence (AI) development and application of AI methods and systems in power engineering. Information and mathematical technologies in science and management, 2021, no. 4, pp. 5–20. doi: 10.38028/ESI.2021.24.4.001.
  16. Gusev K.A., Aldoshin A.V. Modern technologies in the system of sports training. Science-2020, 2022, no. 1, pp. 157–162. EDN: SVKMDX.
  17. Lutoshkin I.V., Paramonova A.A. Analysis of the impact of digital technologies on the development of the national economy. St. Petersburg State Polytechnical University Journal. Economics, 2019, vol. 12, no. 4, pp. 20–31. doi: 10.18721/JE.12402.
  18. Chernykh V.V., Suvorova A.P., Bazhenov R.I. The digital transformation of economic systems – factor in the strategic development of the territories. Bulletin NGIEI, 2019, no. 12, pp. 105–120. EDN: YIWAIC.
  19. Shirokova E.Yu., Leonidova E.G. Assessment of the impact of the technological nature of the regional economy on the dynamics of its development. Scientific journal NRU ITMO. Series “Economics and Environmental Management”, 2022, no. 3, pp. 119–127. EDN: HVHQMF.
  20. Ustinova K.A. Theoretical basis for research of institutional factors for economic development. Russian Journal of Economic Theory, 2020, no. 17, pp. 187–197. doi: 10.31063/2073-6517/2020.17-1.15.
  21. Tanenkova E.N. The opportunities of measurement of institutions and institutional changes in modern economic science. Herald of Omsk University. Series “Economics”, 2020, vol. 18, no. 1, pp. 45–56. doi: 10.24147/1812-3988.2020.18(1).45-56.
  22. Kuzin M.A. Assessing the impact of AI development on the financial sector of the economy. The Eurasian Scientific Journal, 2023, vol. 15, no. S4, pp. 31–41. EDN: SHBCMP.

Supplementary files

Supplementary Files
Action
1. JATS XML
Download

Copyright (c) 2024 Eroshenko E.P.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies