| Аннотация | Artificial intelligence has become an essential element of technological progress, while generative artificial intelligence occupies a special place as an innovative general-purpose technology. Given the rapid development of this technology and its high potential for mass adoption in various economic sectors, it becomes important to assess the impact of this technology on the labor market. The modern Russian labor market is characterized by low unemployment, staff shortages, and intersectoral imbalances. An urgent scientific task is to model scenarios for the development of the labor market in the context of sectors, taking into account the influence of generative artificial intelligence. The aim of the work is to assess the potential impact of the mass use of generative artificial intelligence on the labor market, due to changes in labor efficiency in some professions and industries, based on the analysis of statistical and expert data and economic and mathematical modeling of possible scenarios for the development of the labor market. Economic sectors were divided into three groups depending on the rate of change in personnel needs, based on the analysis of the Beveridge curve, which shows the dependence of the level of needs on the unemployment rate. Using existing statistical data and expert assessments, we determine the degree of influence of generative artificial intelligence on labor efficiency in various industries. We put forward an approach that helps to obtain estimates of possible scenarios for the development of sectoral labor markets for the period up to 2030, based on official forecasts of ministries (Ministry of Economic Development of the Russian Federation, Ministry of Labor of the Russian Federation) for the period up to 2026, their extrapolation, and superimposition of the impact of mass use of generative artificial intelligence (as a disturbing effect). The results obtained suggest that the severity of staff shortage issue in general can be partially reduced by using generative artificial intelligence; thus, we identified industries in which (a) it is possible to address the problem of staff shortage at the current level of needs, and (b) staff shortage will persist. Modeling the migration of professions and personnel between industries seems promising, because the expected effect of mass technology adoption will not only change the balance of labor resources, but also lead to the need to re-profile some of the personnel
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