DefinePK

Abstract

This paper proposes an integrated conceptual framework that connects Artificial Intelligence (AI), Knowledge Management (KM), and Human Resource Management (HRM) to enhance organizational decision-making. Synthesizing empirical insights, the framework demonstrates how AI-enabled KM processes such as knowledge retrieval, sharing, and codification can be leveraged through HRM enablers like organizational learning, employee competencies, and knowledge-based support systems. The model outlines decision-making typologies (automated, augmented, and supported) and incorporates feedback mechanisms for continuous learning and adaptation. Theoretically, the paper contributes to the literature by unifying three traditionally siloed domains, KM, AI, and HRM, through a lens of human-AI collaboration and dynamic capability theory. It extends existing models, such as the SECI framework and rational decision-making paradigms, into a digitally enhanced HRM context. Practically, the framework provides HR leaders with strategic guidance for assessing AI readiness, aligning knowledge systems with workforce capabilities, and implementing ethically responsible AI tools. Key managerial considerations include algorithmic transparency, data governance, and employee engagement through targeted up-skilling and change management initiatives. The paper concludes with a call for empirical validation of the framework across industries and cultural contexts. It highlights the importance of examining ethical implications and the human experience of AI adoption in HRM. Ultimately, the model advocates for a human-centered, adaptive approach to AI integration that augments rather than replaces human expertise in pursuit of more agile, informed, and equitable organizations