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DOI: 10.15862/34FAOR425 (https://doi.org/10.15862/34FAOR425)

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Кочетов Д. С., Досаев Т. Х., Досаев Э. Х. Artificial intelligence as a factor of labor productivity growth in the russian economy: integration problems and long-term potential assessment. Russian journal of resources, conservation and recycling. 2025; 12(s4). Available at: https://resources.today/PDF/34FAOR425.pdf (in Russian). DOI: 10.15862/34FAOR425

Artificial intelligence as a factor of labor productivity growth in the russian economy: integration problems and long-term potential assessment

Kochetov Daniil Sergeevich
Peoples’ Friendship University of Russia named after Patrice Lumumba, Moscow, Russia
E-mail: daniilkochetov@yandex.ru

Dosayev Timur Khanovich
Peoples’ Friendship University of Russia named after Patrice Lumumba, Moscow, Russia
E-mail: conoharendan@mail.ru

Dosayev Emil Khanovich
Federal State University of Education, Moscow, Russia
E-mail: teo.done@bk.ru

Abstract. The article is devoted to the study of the role of artificial intelligence technologies as a tool for increasing labor productivity in the Russian economy, which is experiencing a structural shortage of human resources and a growing lag behind global leaders in terms of the level of robotization in industrial production. The relevance of the topic is determined by the exacerbation of the problem of staff shortages, which reached unprecedented levels in 2024, with 1,5 to 2,6 million unfilled vacancies, depending on the assessment methodology, as well as the need to ensure sustainable economic growth in the face of limited labor resources. The study covers the evolution of scientific understanding of the impact of technological progress on productivity, which involves a differentiated assessment of the effects of automation and the complementarity of labor and capital. It analyzes the phenomenon of the productivity paradox, also known as the Solow paradox, and examines the potential implications of a similar phenomenon in relation to the integration of generative artificial intelligence into business processes. The main theoretical approaches to assessing the macroeconomic effects of artificial intelligence have been systematized, including optimistic forecasts by McKinsey Global Institute and Goldman Sachs, which predict a 7 % increase in global GDP and a 1,5 percentage point increase in productivity annually over a ten-year period, as well as conservative estimates that suggest a GDP increase of only about 1 % over a similar horizon.

Special attention is paid to the institutional, infrastructural, and personnel barriers that hinder the introduction of artificial intelligence technologies in the Russian economy, such as the high cost of implementation, the lack of qualified specialists, the difficulty of integrating AI into existing production processes, and the low density of robotization, which was only 29 units per 10 000 workers in 2024, compared to the global average of 151 units. The National Strategy for the Development of Artificial Intelligence for the period up to 2030, approved by the Decree of the President of the Russian Federation, has been analyzed, and the degree of its implementation has been assessed, taking into account the intermediate indicators of organizations’ expenses on the implementation of relevant technologies. The author has developed a systematization of the channels of artificial intelligence’s impact on labor productivity in the Russian context, taking into account industry-specific features, institutional constraints, and labor market characteristics.

Keywords: artificial intelligence; labor productivity; digital transformation; labor market; staff shortage; robotization; generative neural networks; National Strategy for the Development of Artificial Intelligence; and the productivity paradox

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