AI MEETS HR – SYSTEMATIC REVIEW OF IMPLEMENTATION AND OPERATIONAL BARRIERS

Purpose: This paper aims to explore the main barriers to the adoption and practical functioning of artificial intelligence in HRM. The goal is to provide a structured, multidimensional understanding of the challenges organizations face when implementing AI in HR processes. Design/methodology/approach: The study is based on a systematic literature review of 24 peer-reviewed academic publications from 2020 to 2024. A thematic analysis was employed to identify and categorize barriers, drawing from empirical and conceptual research across different sectors and regions. Findings: The review reveals a complex landscape of barriers spanning psychological, social, organizational, technological, and legal domains. These include lack of digital competencies among HR professionals, poor data quality, resistance to change, low trust in algorithmic systems, and ethical concerns. The findings highlight that AI implementation requires organizational and cultural transformation. Research limitations/implications: The findings are limited by the scope and diversity of the selected literature, which is predominantly English-language and spans various contexts. Practical implications: For successful AI adoption in HR, organizations must invest in digital and analytical skill development, ensure data quality, promote transparency and explainability in AI systems, and actively involve stakeholders in the implementation process. Social implications: The integration of AI into HRM carries significant social implications, particularly regarding fairness, employee autonomy, and workplace relationships. Algorithmic bias may reinforce existing inequalities, while the automation of human-centric processes risks dehumanizing HR practices. Additionally, concerns about privacy, surveillance, and job insecurity can lead to resistance and technostress among employees. Originality/value: This paper contributes a synthesized and structured analysis of current academic insights on AI-related challenges in HRM. It offers a foundation for evidence-based strategies, highlights research gaps, and encourages a systemic, human-centred approach to digital transformation in HR.