Abstract

In the modern economy, digitalization has become one of the key components of the Russian Federation regions socio-economic development. Enterprises of various industries are faced with the need to process large amounts of data, which greatly complicates data management, and therefore the relevance of the analysis of artificial intelligence technologies increases. Training employees for industrial processes is a major challenge in any industry. Effective human resource management requires an accurate assessment and presentation of available competencies, as well as an effective mapping of the required competencies for specific positions. Competences enable the company to achieve high production and economic results. The aim of the study is to develop a structural model of a predictive expert system for managing data on the competencies of a modern manager by combining artificial and human intelligence, which can serve as a decision support tool for managers in real conditions to improve the efficiency of a particular enterprise. The study of the demand for managers and requirements for candidates in the Russian Federation and the Republic of Tatarstan was conducted on the data of the largest Russian Internet recruitment company HeadHunter. To develop a structural model of the proposed expert system, information from specialized scientific publications published in the Russian and foreign scientific literature of the Web of science and Scopus databases was used. The expert system will allow the manager to find the best options for using employees, predict the development of the enterprise as a whole and its individual divisions, which will significantly increase the key performance indicators of any company.

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