Organizational AI Acculturation: How Human‐ AI Interaction Encodes Institutional Knowledge and Builds Competitive Advantage

Abstract

As organizations integrate artificial intelligence into knowledge‐intensive work, a phenomenon is emerging that knowledge management theory has yet to adequately explain: institutional knowledge can become progressively encoded into AI‐enabled organizational infrastructure through sustained patterns of human use. This paper develops that phenomenon into a formal construct, organizational AI acculturation, defined as the process through which an organization's collective knowledge, values, and decision heuristics become embedded in AI‐enabled systems through repeated human interaction, such that the systems' outputs increasingly reflect the organization's distinctive ways of framing problems and evaluating alternatives. The paper makes three contributions. First, it defines the construct and distinguishes it from adjacent concepts, including organizational memory, absorptive capacity, and transactive memory systems. Second, drawing on organizational learning theory, the resource‐based view, and dynamic capabilities, it explains how institutional knowledge encoded into AI‐enabled systems through sustained human use can become a source of competitive advantage when organizations govern the quality and renewal of what their systems encode. Third, it advances four testable propositions linking the quality of human‐AI interaction to competitive advantage, knowledge persistence under employee turnover, and adaptive capacity. Published organizational cases illustrate the construct in practice, showing that deliberate governance of human‐AI interaction can build defensible knowledge assets, whereas poor governance can stabilize error, bias, and outdated assumptions. The paper concludes with a research agenda focused on measurement, mechanism, governance, and scope conditions. The central claim is that knowledge management theory must expand to account for a new kind of knowledge repository: AI‐enabled systems whose behavior is shaped by the cumulative judgments of the organizations that use them.