This paper defines AI Value as a distinct form of value constituted not as realisedeconomic outcome, but as an allocative condition within AI-mediated systems of eval-uation and distribution.Existing value frameworks—profit-based, accounting-based, market-based, and ex-panded disclosure models—remain structurally valid within their respective domains,yet they do not fully capture value under conditions in which allocation is increasinglygoverned by machine-mediated evaluability, admissibility, and future-oriented selection.In response, this paper introduces AI Value as the condition under which an en-tity becomes processable, incorporable, and distributable across systems that allocateattention, capital, credibility, and institutional relevance.The concept is structurally decomposed into four interdependent components: evalu-ability, visibility eligibility, allocability, and temporal projection. Within this structure,profit is repositioned as an interpretable signal component rather than as the definingbasis of value.The paper further situates AI Value within a broader theoretical system linkingAI-Scored Society, AI Indexing Optimisation (AIO), AI Capitalism, and AI Environ-mental Theory, and identifies its institutional implications for valuation systems inwhich allocation precedes or exceeds realised performance.This definition establishes a conceptual framework for analysing value in environ-ments where allocability, rather than profit alone, becomes structurally operative.
Kawazoe Tsutomu (Mon,) studied this question.