Abstract

AI-native organizations increasingly rely on human actors, AI agents, software systems, routines, and governance mechanisms to retrieve, interpret, project, decide from, and revise organizational knowledge. Existing scholarship explains important parts of this phenomenon, including organizational knowledge creation, the knowledge-based theory of the firm, organizational memory, sensemaking, routines, dynamic capabilities, sociotechnical mediation, boundary objects, enterprise ontologies, knowledge graphs, provenance, traceability, organizational digital twins, multi-agent systems, and AI governance. This paper argues that these literatures do not yet provide a complete implementation-independent account of how organizations preserve governed knowledge continuity when AI materially participates in organizational cognition. The paper develops the Organizational Knowledge Kernel as a theoretical construct: a governed, correspondence-preserving organizational knowledge structure through which identity, intent, knowledge, memory, state, representations, projections, decisions, execution, evidence, learning, adaptation, provenance, authority, freshness, confidence, contestability, and lifecycle state remain connected across time. The contribution is integrative and conceptual. The paper defines the construct, distinguishes it from adjacent constructs, presents the conceptual architecture, preserves the fourteen formal propositions from PAPER-009D, and outlines a future evaluation framework without claiming empirical validation.