Designing AI-enabled HR systems: dynamic capabilities, stakeholder legitimacy and human–AI integration

Purpose The purpose of this paper is to examine how HR leaders can design artificial intelligence (AI)-enabled HR systems that generate strategic value while preserving stakeholder legitimacy and enabling effective human–AI collaboration. As AI increasingly shapes recruitment, performance evaluation and workforce analytics, HR leaders must move beyond technology adoption toward capability development, governance design and sociotechnical alignment. Design/methodology/approach The paper adopts a practice-oriented, evidence informed approach by synthesizing contemporary research from dynamic capabilities theory, stakeholder theory and sociotechnical systems theory. These perspectives are translated into a structured framework that guides senior HR leaders in governing AI-enabled HR transformation. Findings AI-enabled HR systems create sustainable organizational value only when three conditions operate together: (1) development of AI-specific dynamic capabilities within HR, (2) institutionalization of stakeholder-oriented governance that maintains legitimacy and trust, and (3) deliberate sociotechnical integration that supports human–AI collaboration. When any of these elements is absent, organizations risk automation bias, stakeholder distrust and misalignment between technology and people. Practical implications HR leaders should build sensing, seizing and transformation capabilities related to AI; formalize governance mechanisms addressing fairness, transparency and accountability; and redesign workflows to ensure structured human oversight and collaboration with AI systems. These actions position HR as a strategic orchestrator of responsible digital transformation. Originality/value This paper integrates three major theoretical lenses rarely combined in HR research and provides a practical roadmap for designing AI-enabled HR systems that balance efficiency, legitimacy and human-centered performance.