2026· SOFT MEASUREMENTS AND COMPUTING· Vol 2/5, pp. 93-101· 0 citations
Abstract
The article explores the transformative role of artificial intelligence technologies in three key functional areas of human capital management – recruitment, evaluation and employee development, with an emphasis on systematizing theoretical and applied approaches to integrating AI into personnel processes, as well as analyzing both the strategic advantages and ethical and organizational limitations of algorithmization of personnel management. The relevance of the study is due to the fundamental transformation of HR work under the influence of large language models and machine learning methods, when organizations are increasingly turning to AI to solve routine tasks, from automatic resume screening to forecasting turnover and personalization of development programs, and, according to systematic reviews, 33 percent of organizations have already implemented AI tools in talent management, however only 16 percent use these technologies optimally to achieve organizational results.
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
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
It was found that the introduction of AI facilitates the transition to a predictive management model, increases forecasting accuracy, reduces transaction costs and strengthens control over business processes.
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
A framework for responsible AI deployment consisting of six components: defining purpose and risk levels; data governance; relevance and fairness assessment; ensuring human oversight and decision-making; transparency and review; and continuous monitoring and capacity building is proposed.
H. Nguyen· International Journal of Sci...· 0 citations
The article addresses the conceptual problem of how managerial work should be understood when analytical and supervisory activities are partly transferred to intelligent systems and considers the competencies required for interpreting algorithmic outputs, coordinating human and digital actors, managing organizational c...
M. Lyzak· Eastern Europe: Economy, Bus...· 0 citations
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