Artificial Intelligence in Human Talent Management and its Strategic Impact on Human Resources Decision-Making: A Systematic Literature Review

Gasparrini-Cañas V.G.; Hernández-Hernández G.Y.; Pérez-Vargas A.A.; Mendoza-Vara A.N.; Sánchez-Aquituari A.M.; Gonzalez-López A. · CEUR Workshop Proceedings (2026)

Resumen

This study analyzes the impact of artificial intelligence (AI) on strategic decision-making in human resource management (HRM), based on evidence from the scientific literature. The research followed PRISMA guidelines and the PICOC framework, including 20 peer-reviewed studies retrieved from databases such as Scopus, Web of Science, and Science Direct. Findings indicate that the main applications of AI in HRM focus on recruitment, selection, performance evaluation, training, and employee retention, enhancing efficiency, accuracy, and agility in decision-making. The review highlights benefits such as the reduction of human bias and the strengthening of predictive analytics. However, significant challenges remain, particularly organizational resistance, algorithmic opacity, and the demand for new digital skills. From an ethical perspective, the results emphasize the urgency of governance frameworks that ensure transparency, fairness, and the active participation of employees in AI-based HR processes. The study concludes that AI is no longer a distant promise but a present reality that structurally reshapes the role of HR. Nevertheless, its strategic value can only be fully realized when integrated ethically, critically, and collaboratively, combining technological capabilities with human judgment. This review provides a useful framework for both researchers and practitioners seeking to implement AI solutions in HRM effectively and sustainably.

Instituciones: Universidad Autónoma del Perú