Enterprise frameworks for artificial intelligence (AI) now broadly agree that value derives from organizationalsystems rather than from models — a thesis once differentiating and now consensus across consultancy heuristics, standards bodies,and the productivity-paradox literature. That agreement has obscured a structural gap: existing frameworks resolve the systemsover-models question by enumerating capabilities, ranking maturity stages, or stacking measurement layers, but they do not specifywhich organizational elements bind the value of AI, or in what relation. This article presents the AI Value System, an organizationaloperating model in which a living Knowledge layer and a Governance layer form an enabling base, Coordination and Orchestrationconstitute the engine that runs work, Human Adoption is a cross-cutting condition that runs through every layer and determineswhether value is realized, and Value itself — defined as outcome net of total cost — emerges from the functioning whole and feedsback into the next decision. The framework's central claim is that two of these elements bind value while prevailing frameworksunderbuild them: Coordination, which existing frameworks tend to leave implicit, under-specified, or subordinated to workflow andintegration language rather than naming as a first-class layer, and Human Adoption, which most frameworks measure but few treatas a designed, system-wide condition. Within Adoption, the paper isolates human judgment — the calibrated exercise of thediscretion each layer leaves to people — as the specific human capacity through which the condition operates, and the one whoseimportance rises rather than falls as orchestration automates. An operating model that does not architect these two forfeits value itsmodels are technically capable of producing, irrespective of model quality or governance maturity. The contribution is not the claimthat organization matters; it is a specification of which layers bind, how they relate, and why governance and coordinationaccelerate rather than constrain the realization of value. This is a conceptual, theory-building contribution: it advances and groundsa falsifiable framework and specifies the study that would test it, but reports no empirical validation here.
Elena Millan Ortega (Sun,) studied this question.