2026· SOFT MEASUREMENTS AND COMPUTING· Vol 6/5, pp. 82-89· 0 citations
Abstract
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.
The present study focuses on the systematization of mathematical approaches to modeling the dynamics of AI development as a technological phenomenon, including logistic and multilogistic models, methods based on the analysis of scientific publications and approaches using deep learning to predict the growth of technolo...
Akhmed M. Gachaev· EKONOMIKA I UPRAVLENIE: PROB...· 0 citations
An integrative analysis of the performance of Artificial Intelligence in Human Resource Management gives the use of AI-led tools such as machine learning (ML) and natural language processing (NLP) in optimizing the hiring process and improving decision-making effectiveness.
Nikhil Thakur, Sandip Ghodke· International Journal of Inn...· 0 citations
Background. The growth of technical characteristics of artificial intelligence (AI)-based systems and the expansion of demand from enterprises occur with simultaneously growing development restrictions. The article is devoted to identifying growth barriers, analyzing approaches to reducing their impact, developing reco...
Mikhail Yu. Mikheev, Oleg V. Prokofiev, Irina Yu. Semochkina· Reliability and Quality of C...· 0 citations
The analysis closely examined the most-cited empirical studies to identify AI applications in talent development and talent management functions, and found them in learning and skills development, talent acquisition and selection, talent retention, attrition prediction, and employee performance and engagement.
Azza Al Hajri, Dana Alharbi· International Journal of AI...· 0 citations
Evidence is provided that AI can substitute codifiable tasks, create jobs in AI and the digital economy, and increase employee productivity through human-machine cooperation, Nevertheless, these AI effects are not equally distributed.
Hongjie Chen, Zhen-Wei Tang· Journal of Applied Economics...· 0 citations
It is concluded that AI is no longer a distant promise but a present reality that structurally reshapes the role of HR, and its strategic value can only be fully realized when integrated ethically, critically, and collaboratively, combining technological capabilities with human judgment.
Victor Gerardo Gasparrini-Cañas, Gladys Y. Hernández Hernández, Andrés Alejandro Pérez-Vargas et al.· 0 citations
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