ASSESSMENT OF OPERATIONAL COSTS REDUCTION IN HUMAN CAPITAL MANAGEMENT THROUGH IMPLEMENTATION OF AI MODELS IN RECRUITMENT AND SELECTION PROCESSES

Abstract

The article examines the problem of optimizing operating costs for human capital management in conditions of a structural shortage of labor resources and macroeconomic instability. The purpose of the study is to develop and test a methodological approach to assessing the economic effect of introducing artificial intelligence models into the processes of personnel search and selection, including the calculation of key financial metrics. In conditions of acute personnel shortages and economic instability, companies are increasingly turning to artificial intelligence to optimize recruitment costs. However, there is still no clear understanding of how exactly to evaluate the financial return on such investments. The article proposes a methodological approach that allows you to calculate savings from the introduction of AI in recruiting using indicators of the cost of hiring, return on investment and payback period.