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AI-Mediated Revenue Share (AMRS)

AMRS = R_AI / (R_AI + R_H) — The proportion of total revenue transacted through AI-mediated channels versus human-mediated channels.

Description

AI-Mediated Revenue Share measures the economic shift from human-mediated to AI-mediated commerce. AMRS = R_AI / (R_AI + R_H) where R_AI is AI-mediated revenue and R_H is human-mediated revenue. Rising AMRS indicates structural economic transition to AI intermediation.

Related Concepts

Computational Conversion (CC)Zero-Click Exposure (ZCE)ai-mediated-action

Related Research

AI-Mediated Property Discovery Report 2026

The AI-Mediated Property Discovery Report 2026 presents the first comprehensive observational study of how AI systems discover, evaluate, compare, and select properties across diverse markets. Through systematic observation of AI response patterns across 50 real estate markets, thousands of AI responses, and documented selection events, this report establishes the empirical foundation for understanding AI-mediated property discovery. The report analyzes property selection behavior, identifies top selection signals, examines explainability patterns, measures representation effects, and documents citation sources that inform AI decision-making.

The Zero-Click Economy

The Zero-Click Economy examines how AI-mediated discovery, selection, recommendation, verification, and action alter the transmission of economic signals from policy and demand to firms, assets, households, sectors, and jurisdictions. We introduce the Current Reporting-Period Hypothesis, which states that AI systems construct consideration sets from representations as they exist at inference time, not from the period the policy or demand signal was emitted. This creates Computational Transmission Attrition—policy or demand-induced signals may attenuate, misallocate, or leak before reaching intended economic targets. We formalize Dynamic Computational Risk as the interaction between exposure (dependence on AI-mediated allocation), technological velocity (rate of change in AI-mediated discovery), financial sensitivity (margin of capital, liquidity dependence), and adaptation capacity (speed of organizational response). The paper consolidates the Representation Economy measurement stack: Agent Readiness Index (ARI), Global Agent Readiness Index (GARI), Zero-Click Exposure Index (ZCEI), Platform Dependency Index (PDI), Computational Business Risk Index (CBRI), Dynamic Computational Risk Index (DCRI), Enterprise Adaptation Velocity Index (EAVI), Computable Asset Ratio (CAR), National Computable Economy Index (NCEI), Sovereign Adaptation Velocity Index (SAVI), and sovereign outputs including Compound Regional Adaptation Velocity Index (CRAVI), Global Computable Economy Index (GCEI), Sovereign Adaptation Gap (SAG), and Dynamic Monetary Sovereignty Risk Index (DMSRI).