This article examines the impact of the introduction of artificial intelligence on the structure and quality of human capital in the digital economy. The relevance of the research is due to the fundamental transformation of the labor market caused by the rapid spread of AI technologies, which creates both new opportunities for increasing labor productivity and serious challenges for the system of vocational education and retraining. Unlike the works focused on the technological aspects of AI or on macroeconomic employment forecasts, the present study focuses on structural changes in human capital – the transformation of skill requirements, the redistribution between cognitive and non-cognitive competencies, as well as the adaptive strategies of employees and firms. The purpose of the work is to systematize modern empirical and theoretical studies of the impact of AI on human capital and to substantiate the directions of its qualitative transformation.
Svetlana A. Gusarova, T. Skryl, D. Kurazova· SOFT MEASUREMENTS AND COMPUT...· 0 citations
The article explores the potential of using artificial intelligence technologies to assess and predict the development of human capital in an organization, with an emphasis not on technological aspects per se, but on a conceptual understanding of how AI is transforming approaches to personnel management, creating opportunities for the transition from reactive, historical data-based practices to proactive, predictive talent management systems, and how this preserves the central role of human judgment in interpreting and validating the results of algorithmic analysis. The relevance of the study is due to the rapid spread of AI technologies in the field of human resource management, where, according to empirical studies, 89 percent of organizations intend to maintain or increase investments in AI despite economic uncertainty, and hybrid skills combining technical competence with developed "soft" skills such as critical thinking, adaptability, and emotional intelligence, the evaluation of which remains a challenging task for algorithmic systems. In contrast to the work focused on the development of specific algorithms or on regulatory issues of AI ethics, the present study focuses on the systematization of modern approaches to the use of AI in the assessment and forecasting of human capital, on identifying key areas of its application, including forecasting staff turnover, human resource assessment and long-term workforce planning, as well as on the justification of the need for hybrid models that combine algorithmic efficiency with human judgment.
D. Kurazova, Z. Troska, L. Tochieva· SOFT MEASUREMENTS AND COMPUT...· 0 citations