From Knowledge Assets to Epistemic Capital: Human–AI Collective Intelligence in Organizations

Abstract

As organizations increasingly integrate artificial intelligence into decision-making and knowledge work, traditional notions of knowledge assets are no longer sufficient to explain how value is created, sustained, and leveraged. This paper advances a conceptual shift from knowledge assets to epistemic capital, defined as the collectively produced, context-sensitive, and action-oriented capacity to generate, validate, and apply knowledge within human–AI systems. We argue that epistemic capital emerges not from isolated human expertise or standalone AI capabilities, but from their dynamic interaction within organizational settings. Building on theories of collective intelligence, organizational knowledge, and socio-technical systems, the paper conceptualizes Human–AI Collective Intelligence as an epistemic infrastructure through which organizations accumulate, transform, and deploy epistemic capital. The framework highlights key dimensions of epistemic capital including epistemic diversity, validation mechanisms, interpretability, and governance and explains how these dimensions shape the quality of organizational decision-making. By reframing Human–AI collaboration as a process of epistemic capital formation rather than mere knowledge management or automation, this study offers a theoretical foundation for understanding intelligence as a strategic organizational resource. The paper contributes to research on organizational intelligence, AI-enabled decision-making, and knowledge-based theory of the firm, while providing implications for the design, governance, and ethical deployment of Human–AI systems in modern organizations.

Keywords: Epistemic Capital; Human–AI Collective Intelligence; Organizational Decision-Making; Knowledge Assets; Hybrid Intelligence Systems; Organizational Knowledge; Socio-Technical Systems; AI Governance; Collective Cognition; Strategic Decision-Making