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Computational Eligibility (CE)

CE(e) — The condition of being discoverable, interpretable, comparable, verifiable, permissioned, and actionable by artificial agents. Also referred to as AI Eligibility.

Description

Computational Eligibility is the access condition for AI-mediated markets. An object that is computationally eligible can be discovered, evaluated, and acted upon by AI systems. ARI operationalizes CE as a measurable index. The Balance-Sheet Economics paper extends this concept to include probabilistic assessment (0 ≤ AE ≤ 1) and its relationship to Qualified Demand Capture.

Related Concepts

agent_readiness_indexglobal_agent_readiness_indexcomputational_admissibilityrepresentation_deficit

Related Research

Agent-Ready Market Infrastructure

Agent-Ready Market Infrastructure introduces the infrastructure layer for AI-mediated economies, specifying how economic entities, assets, and services can become discoverable, interpretable, comparable, verifiable, permissioned, and transaction-capable for AI agents. This document defines the Agent-Readiness Index (ARI) as a multiplicative measurement framework, the Global Agent-Readiness Index (GARI) for cross-border market access, universal Verified Property Records as persistent portable representation, jurisdictional legibility for legal interoperability, semantic portability for cross-system understanding, and computational eligibility as the prerequisite condition for allocative participation.

The Balance-Sheet Economics of AI-Mediated Demand

The migration of discovery and comparison from human-mediated search to AI-generated answers and agentic interfaces may alter the economics of acquiring and distributing demand in physical-asset markets. This paper examines how AI-mediated demand formation could affect customer acquisition costs, distribution dependency, contribution margins, and asset productivity in real estate and hospitality. We propose that zero-click—initially observed as a traffic problem—may transmit structurally into distribution cost inflation and ultimately appear as margin pressure. We formalize a transmission mechanism in which representation deficits may transmit through demand leakage, distribution dependency, and acquisition-cost inflation to contribution-margin compression, while lower qualified-demand capture may separately affect occupancy, time-to-match, and asset productivity. Contribution margin and asset productivity may subsequently interact through operating and reinvestment feedback effects. The paper introduces a measurement architecture designed for empirical validation: representation quality (VIS), readiness (GARI), market outcomes (ARS, PDD, CDL), financial impact (RAAC, CMP, RROI), and exploratory composite indices. The Verified Property Representation (VPR) is positioned as a proposed persistent representation layer intended to improve computational legibility—a testable intervention through which the paper's hypotheses may be validated.