Knowledge Creation in the Age of Agentic AI: Rethinking KMS for Adaptive Organizations

Abstract

The rapid emergence of agentic artificial intelligence (AI) systems—capable of autonomous goal-setting, reasoning, and action—marks a pivotal shift in organizational knowledge creation. Traditional Knowledge Management Systems (KMS) were designed to capture, store, and retrieve explicit knowledge within relatively stable environments. However, in the age of agentic AI, knowledge is no longer static; it is dynamically generated, synthesized, and operationalized through continuous human–AI collaboration. This article examines how agentic AI reshapes the processes of knowledge creation, transfer, and application within adaptive organizations. Drawing on knowledge-based theory of the firm, sociotechnical systems perspectives, and emerging AI governance frameworks, we propose a rethinking of KMS architecture to support real-time learning, distributed intelligence, and augmented decision-making. We introduce a conceptual model of Agentic Knowledge Ecosystems (AKE), in which humans and AI agents co-create knowledge through iterative feedback loops, contextual reasoning, and embedded organizational memory. The paper outlines key design principles—including transparency, traceability, adaptive learning, and ethical oversight—and discusses implications for leadership, organizational culture, and digital infrastructure. By reconceptualizing KMS as dynamic, agent-enabled ecosystems rather than static repositories, organizations can enhance resilience, innovation capacity, and strategic adaptability in increasingly complex environments.

Keywords: Agentic AI; Knowledge Management Systems (KMS); Knowledge Creation; Adaptive Organizations; Human–AI Collaboration; Organizational Learning; Sociotechnical Systems; Digital Transformation; Intelligent Agents; AI Governance.