Forecast of Staffing Needs for the Artificial Intelligence Sector in Russia

A. O. Aver’yanov (), I. S. Stepus’ and V. A. Gurtov
Additional contact information
A. O. Aver’yanov: Budget Monitoring Center, Petrozavodsk State University
I. S. Stepus’: Budget Monitoring Center, Petrozavodsk State University
V. A. Gurtov: Budget Monitoring Center, Petrozavodsk State University

Studies on Russian Economic Development, 2023, vol. 34, issue 1, 86-95

Abstract: Abstract— The article presents a science-based approach to assessing the staffing needs for the artificial intelligence sector in Russia by the analogy method. The use of the method is justified by the lack of basic indicators for the economy and the labor market of the AI sector in Russian economic statistics and other sources. The selection of a benchmark country for the transfer of the AI indicator structure to the Russian labor market was based on three factors, i.e., availability of national labor market data, similarity of the employment structure in the economy, and comparable publication activity. Based on the developed methodological approaches, quantitative indicators of the average annual number of employees for the medium-term period up to 2025, as well as indicators of additional annual staffing requirements for the first time have been created for the Russian AI sector.

Keywords: artificial intelligence; labor market; staffing needs forecast; analogy method (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1134/S1075700723010021 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sorede:v:34:y:2023:i:1:d:10.1134_s1075700723010021

Ordering information: This journal article can be ordered from
https://www.springer ... nomics/journal/11507

DOI: 10.1134/S1075700723010021

Access Statistics for this article

Studies on Russian Economic Development is currently edited by Viktor V. Ivanter, Dmitrii B. Kuvalin and Galina A. Yaremenko

More articles in Studies on Russian Economic Development from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().