The subject of the research is the impact of artificial intelligence technologies on the transformation of the labor market in the Russian Federation amid accelerated digitalization of the economy and the implementation of AI in production, management, and service processes. It examines how algorithmization and the use of AI tools change the structure of labor demand, the content of labor functions, the requirements for employee qualifications, as well as the mechanisms for personnel selection and evaluation. The current indicators of the Russian labor market are analyzed, reflecting the combination of record-low unemployment with a persistent labor shortage and pronounced professional-qualification and regional imbalances. Special attention is given to the influencing factors of AI, including the automation of routine operations, productivity growth, the formation of hybrid professions, and the intensification of employment segmentation. It is shown that, in the future, a key outcome will be the redistribution of labor functions and the complexity of the competency model, rather than direct mass displacement of employment, which raises the tasks of proactive adaptation of labor market institutions. The methodological basis of the research consists of general scientific methods of analysis, synthesis, comparison, and generalization, as well as methods of statistical and structural analysis, applied to assess labor market indicators. A systemic approach was used, ensuring the examination of the impact of AI in relation to technological factors, socio-economic consequences, and institutional mechanisms for employment regulation. The scientific novelty lies in the systematization of the factors influencing artificial intelligence on the Russian labor market and in substantiating the logic of employment transformation as a structural process manifested in changes in the nature of work, qualification demand, and models of employment organization. Key directions of expected transformations are formulated: the expansion of hybrid professional roles, the increasing importance of AI competencies and data handling skills, the development of flexible forms of employment, and the algorithmization of management practices. It is shown that the uneven implementation of AI intensifies the risks of employment and income polarization, as well as the entrenchment of professional-qualification mismatches. The conclusion is made about the feasibility of implementing a set of adaptation measures, including the development of a national system of continuous education, the stimulation of corporate retraining, the updating of professional standards considering AI competencies, and the formation of principles for the transparent and responsible application of AI in labor relations.
Semyon Dmitrievich Nazarov (Thu,) studied this question.