ARTIFICIAL INTELLIGENCE IN PERSONNEL SELECTION: A LITERATURE REVIEW OF ORGANIZATIONAL PSYCHOLOGY

Abstract

Introduction. Artificial Intelligence (AI) has become integral to modern HR processes, particularly in personnel selection. Its integration enables the automation and optimization of traditional hiring approaches, reducing costs and enhancing process efficiency. Technologies such as machine learning, natural language processing (NLP), computer vision, and large language models (LLMs) facilitate resume analysis, candidate evaluation, job-fit prediction, and interview automation. Objective. The study aims to systematize existing knowledge about the use of AI in personnel selection, identify its advantages and challenges, and highlight gaps in the scientific literature for future research. Methods. A systematic literature review was conducted, analyzing 61 scientific articles from leading databases (PsycINFO, WoS, Scopus, Google Scholar). Results. Key AI applications include automated resume screening, chatbot communication, predictive analytics, and behavioral analysis during interviews. AI systems analyze psychological aspects such as personality traits, cognitive abilities, emotional intelligence, social skills, motivation, and cultural fit. Advantages include cost reduction, shorter hiring times, and improved candidate experience. However, challenges such as algorithmic bias and ethical concerns persist. Conclusions. AI in personnel selection has the potential to enhance the efficiency and quality of hiring processes significantly. However, its implementation requires a balanced approach considering ethical, legal, and social factors. Future research should focus on developing transparent and fair algorithms, assessing the long-term impact of AI on organizations and candidates, and exploring its adaptation to the specific needs of various industries and cultures.

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