Artificial Intelligence in Human Resource Management: A Systematic Literature Review, Integrative Framework, and Future Research Agenda

Abstract

Artificial intelligence (AI) is reshaping Human Resource Management (HRM) by transforming how organizations acquire, develop, deploy, evaluate, and retain human capital while expanding HR’s strategic role in decision-making and value creation. Despite growing scholarly attention, AI-driven HRM research remains fragmented across HR functions, theoretical perspectives, technological capabilities, and organizational contexts, limiting understanding of how AI creates value, through which mechanisms it influences employee and organizational outcomes, and under what conditions these effects emerge. This study addresses these limitations through a systematic literature review of research on AI-driven HRM published between 2011 and 1 July 2026. The review critically synthesizes the evolution, applications, enabling capabilities, value-creation mechanisms, implementation conditions, and outcomes of AI-driven HRM, with particular attention to human–AI collaboration, organizational readiness, leadership, organizational culture, AI literacy, employee trust, workforce adaptability, and responsible AI governance. It identifies key conceptual, theoretical, empirical, methodological, and contextual gaps and develops a structured agenda for future research. Building on the synthesized evidence, the study proposes an integrative framework that conceptualizes AI-driven HRM as a dynamic socio-technical capability through which AI-enabled technological resources are orchestrated with strategic HR practices, human capabilities, leadership and culture, responsible AI governance, and continuous learning to generate sustainable employee and organizational value. Contextual conditions and governance mechanisms are positioned as critical boundary conditions shaping these relationships. Lean Six Sigma DMAIC is incorporated as a complementary continuous-improvement mechanism to support the systematic measurement, analysis, improvement, and control of AI-enabled HR processes. The study advances AI-HRM scholarship by moving beyond technology-centric and function-specific perspectives toward an integrated, human-centered, strategically embedded, and responsibly governed understanding of AI-driven HRM, while providing a theoretically grounded foundation for future empirical research and sustainable organizational value creation.