Artificial Intelligence and the Ethical Boundaries of Managerial Judgment: Insights from a Systematic Literature Review

Abstract

This research aims to systematically analyze the utilization of Artificial Intelligence (AI) in various Human Resource Management (HRM) functions, evaluate the theoretical foundations used in previous studies, summarize key empirical findings, and identify research gaps and emerging ethical-managerial implications. The research uses a Systematic Literature Review (SLR) design with a PRISMA approach. Data was collected from the Scopus, Web of Science, and Google Scholar databases for reputable journal articles published between 2015 and 2025. The selection process was conducted through the stages of identification, screening, and eligibility based on strict inclusion and exclusion criteria, resulting in 52 articles that were analyzed using thematic analysis and conceptual synthesis. Theoretically, this research enriches the technology-based HRM literature by presenting a typology of AI utilization in HRM functions and revealing the limitations of the theoretical framework, which is still partial and fragmented in previous studies. The research findings have strategic implications for practitioners and policymakers in ethically, responsibly, and sustainably integrating AI into HRM practices, particularly in the context of recruitment and selection, performance analytics, talent management, and data-driven HR decision-making. The limitations of this study lie in its reliance on secondary data sources and the dominance of studies focused on developed country contexts. This situation opens opportunities for further research that is empirical, longitudinal, and contextual, particularly in developing countries.

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