Artificial Intelligence (AI) in Human Resource Management (HRM), Research Development and Implementation Barriers: A Systematic Literature Review

Abstract

The advancement of Artificial Intelligence (AI) has transformed various Human Resource Management (HRM) functions, from recruitment and selection to data-driven decision-making. Despite the growing number of studies, findings remain fragmented across different contexts, and comprehensive syntheses linking research trends, benefits, and implementation barriers remain limited underscoring the novelty of this study in offering an integrated, PRISMA-based synthesis of the field. This study aims to map the development of AI research in HRM, identify the benefits of AI adoption, and analyze implementation barriers through a Systematic Literature Review (SLR) based on the PRISMA 2020 guidelines. A systematic search was conducted in the ScienceDirect and Google Scholar database. After applying predefined inclusion and exclusion criteria covering relevance to AI-HRM integration, publication type (peer-reviewed journal articles), and methodological quality the articles were screened through title, abstract, and full-text review, resulting in ten studies selected for descriptive and thematic synthesis. The findings reveal a growing research trend, characterized by the dominance of quantitative approaches and a focus on AI-based recruitment and selection, AI adoption, and HR analytics. AI implementation improves HRM efficiency, enhances data-driven decision-making, and supports employee competency development. However, organizations continue to face challenges, including algorithmic bias, limited data quality, insufficient organizational readiness, inadequate digital competencies, and concerns regarding ethics and trust. The study concludes that successful AI implementation in HRM depends on balancing technological capabilities, organizational readiness, and human resource competencies. These findings provide practical implications for organizations in developing effective AI implementation strategies and offer directions for future research by expanding investigations into developing-country contexts, broader HRM functions, and ethical issues related to AI adoption.