The anticommons of knowledge: a new perspective for the AI-HI era

Purpose This viewpoint paper aims to introduce a novel conceptual framework for understanding knowledge sharing in the AI-HI era, arguing that conventional metaphors such as the “knowledge commons” obscure the real structural tensions in knowledge governance. It reframes the debate through the lens of the tragedy of the anticommons (TOAC) and proposes the underexplored concept of negative rivalry in use (negative-RIU) as a defining property of knowledge. Design/methodology/approach The paper adopts a critical and integrative approach, combining insights from knowledge management, transaction cost economics, intellectual property theory and Eastern dialectical thinking. It challenges the traditional application of material asset protection logic to knowledge and develops a systemic understanding of knowledge co-creation and value generation. Findings Knowledge, unlike physical goods, usually improves through use. Overprotection via fragmented intellectual property rights leads to TOAC, inhibiting innovation and collaboration. A cross-case analysis reveals that the conflict between knowledge’s negative-RIU and high excludability underpins this tragedy, while a portfolio of governance mechanisms – from strategic openness to community self-organization – can facilitate sharing. Practical implications This perspective supports a more balanced and adaptive approach to knowledge management. It provides a KM design checklist to help organizations and policymakers align legal, organizational and technological systems with the negative-RIU nature of knowledge in AI-driven environments, thereby mitigating the risks of the anticommons. Originality/value By introducing and applying the concept of negative-RIU to knowledge management, the paper offers a timely and impactful theoretical reorientation. It provides a foundational framework for revising KM practices and policies through mechanisms and principles that better harness the collaborative potential of the AI-HI integration era.