Inteligencia artificial en la mejora del talento humano y gestión del conocimiento en organizaciones: una revisión sistemática en Scopus

José del Carmen López-Urbina

doi:10.51252/rcsi.v5i1.889

Authors

José del Carmen López-Urbina Universidad César Vallejo https://orcid.org/0000-0003-0770-752X

DOI:

https://doi.org/10.51252/rcsi.v5i1.889

Keywords:

business management, knowledge automation, performance evaluation, technological innovation, workforce optimization

Abstract

This study analyzes the application of artificial intelligence (AI) in talent management and organizational knowledge through a systematic review of 50 scientific articles indexed in Scopus. A documentary review methodology was employed, with selection criteria based on relevance and recent contributions. The main AI applications identified include the optimization of administrative processes, the personalization of training programs, and data-driven strategic decision-making. Key approaches analyzed include machine learning, data mining, and expert systems, which have improved performance evaluation, personnel selection, and knowledge management. The results indicate that AI has increased efficiency in talent management, though challenges persist, such as data quality, organizational resistance, and biases in selection algorithms. The study concludes that AI adoption in human resources continues to grow, promoting more adaptive management models. However, it is essential to address its limitations through regulatory frameworks and oversight strategies to ensure an ethical, fair, and goal-aligned implementation within organizations.

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