Zero-Click and Computational Transmission Primitives
Volume XII: Primitives for analyzing the Zero-Click Economy, computational transmission gaps, and value reallocation in AI-mediated markets. These primitives measure how demand, visibility, and value flow through AI systems.
Primitives (49)
Computational Selection (CS)
CS(e) — The process by which AI systems evaluate and select assets for inclusion in consideration sets, independent of human browsing or clicking.
Computational Recommendation (CR)
CR(e) — The stage where AI systems present selected options to users with explanations and rationale for the recommendation.
Computational Verification (CV)
CV(e) — The process by which AI systems verify claims, trust signals, and preconditions before recommending or acting on assets.
Computational Actionability (CAc)
CAc(e) — The extent to which AI systems can initiate or coordinate transactions on behalf of users, subject to authorization and safety constraints.
Computational Conversion (CC)
CC — The rate at which AI-mediated selection and recommendation convert into actual transactions or economic outcomes.
Potential Demand (PD)
PD — Economic demand that exists or could exist but is not realized through AI-mediated channels due to exclusion, friction, or transmission gaps.
Realised Demand (RD)
RD — Economic demand that successfully completes the AI-mediated funnel from discovery through selection to transaction.
Transmission Coefficient (TE)
TE = RD / PD — The ratio of realised demand to potential demand, measuring how effectively economic demand transmits through AI-mediated channels.
Computational Transmission Gap (CTG)
CTG = PD - RD — The portion of potential economic demand that is lost due to exclusion, friction, or gaps in AI-mediated channels. Also referred to as Computational Demand Leakage.
Visibility Transmission Gap (VTG)
VTG — The portion of assets that are visible online but not discoverable by AI systems through computational search.
Selection Transmission Gap (STG)
STG — The portion of AI-discovered assets that are not selected or recommended by AI systems for user consideration.
Recommendation Transmission Gap (RTG)
RTG — The portion of AI-selected assets that are not recommended to users or where recommendations fail to convert to user consideration.
Verification Transmission Gap (VtG)
VtG — The portion of recommended assets where users or AI systems cannot verify claims or preconditions before taking action.
Action Transmission Gap (ATG)
ATG — The portion of verified assets where transactions cannot be completed due to action protocol gaps, authorization failures, or missing infrastructure.
Revenue Realisation Gap (RRG)
RRG — The portion of economic value that exists but is not captured as revenue due to AI-mediated transmission failures.
Citation Transmission Branch (CtB)
CtB — The phenomenon where assets are cited or referenced by AI systems but not transmitted through to economic transactions or revenue capture.
Computational Visibility Loss (CVL)
CVL — The degradation or complete loss of AI-mediated visibility due to representation decay, canonical drift, or platform dependency.
Computational Access Gap (CAG)
CAG — The disparity between online presence and AI-mediated access, where assets exist online but cannot be discovered or selected by AI systems.
Economic Recommendation Loss (ERL)
ERL — The economic value lost when AI systems recommend alternatives over economically optimal choices due to representation quality or algorithmic bias.
Inference Burden (IB)
IB — The computational cost and complexity required for AI systems to extract, infer, or reconstruct information from representations.
Token Efficiency (TEf)
TEf — The amount of useful information extracted per unit of computational cost (tokens) in AI-mediated processing.
Computational Liquidity (CL)
CL — The ease with which assets can be discovered, evaluated, compared, and transacted by AI systems in AI-mediated markets.
AI Allocability (AA)
AA — The extent to which economic entities, assets, or services can be allocated by AI systems in consideration sets and decision processes.
AI Allocability Discount (AAD)
AAD — The reduction in economic value or market access for assets with low AI allocability, independent of their fundamental economic quality.
Platform Dependency (PD)
PD — The extent to which AI-mediated access and allocability depend on specific platforms, infrastructures, or intermediaries.
Zero-Click Exposure (ZCE)
ZCE — The degree to which economic entities are exposed to AI-mediated allocation without human intermediate clicking or browsing.
Computational Business Risk (CBR)
CBR — The risk to business continuity and revenue from AI-mediated market dynamics, including exclusion, transmission loss, and algorithmic dependence.
Dynamic Computational Risk (DCR)
DCR — Time-varying risk to economic actors from AI-mediated market dynamics, including algorithm changes, representation decay, and competitive exclusion.
Enterprise Adaptation Velocity (EAV)
EAV — The speed at which organizations can improve representation quality, add verification infrastructure, and increase AI allocability.
Technological Velocity (TV)
TV — The rate of change in AI system capabilities, representation standards, and market infrastructure that affects allocability over time.
Adaptation Velocity (AV)
AV — The rate at which economic entities can improve their AI allocability through representation enhancement, verification infrastructure, and protocol adoption.
Computable Asset (CA)
CA — An economic asset or entity encoded as machine-readable information that AI systems can discover, evaluate, compare, and transact.
Computable Asset Ratio (CAR)
CAR = CA / TA — The proportion of total assets in an economy or portfolio that are computable (machine-readable, verifiable, transaction-capable for AI systems).
National Computability (NC)
NC — The degree to which a national economy has machine-readable, verifiable, and transaction-capable representations across its asset base, institutions, and infrastructure.
Sovereign Adaptation Velocity (SAV)
SAV — The speed at which nations, jurisdictions, or sovereign entities can improve representation infrastructure, verification systems, and AI-readiness across their economic base.
Sovereign Adaptation Gap (SAG)
SAG = TV - SAV — The gap between technological change velocity and sovereign adaptation velocity, creating vulnerability to AI-mediated exclusion.
Monetary Velocity Gap (MVG)
MVG — The reduction in monetary policy effectiveness due to computational transmission gaps, AI-mediated allocation, and sovereign exposure to external AI systems.
Dynamic Monetary Sovereignty Risk (DMSR)
DMSR(j) = f(EAD, CTG, SAG, MPE) — Sovereign risk arising from external AI dependency, computational transmission gaps, adaptation velocity, and monetary policy effectiveness constraints.
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.
Representation Selection Elasticity (RSE)
RSE — The sensitivity of AI-mediated selection outcomes to changes in representation quality, measured as the change in selection probability per unit change in representation metrics.
Inference Cost per Successful Action (ICSA)
ICSA = TC / SA — The computational cost incurred per successful action or transaction mediated by AI systems.
Computational Revenue at Risk (CRAR)
CRAR — The revenue exposed to loss or reduction due to poor AI allocability, representation gaps, or computational transmission failures.
Representation Return on Investment (R-ROI)
R-ROI = (Gains - Costs) / Representation Investment Costs — The economic return on investment in representation quality improvements for AI-mediated markets.
Cross-Border Computational Reallocation (CBCR)
CBCR — The extent to which AI-mediated allocation redirects economic demand across jurisdictional borders, favoring some regions over others.
Acquisition-Cost Inflation
A persistent increase in acquisition or distribution cost per qualified outcome associated with greater reliance on paid or intermediated demand channels.
Margin–Productivity Feedback
A potentially bidirectional feedback relationship through which contribution margin and asset productivity interact via pricing, utilization, operating leverage, maintenance, and reinvestment.
Balance-Sheet Transmission
The proposed pathway through which persistent changes in distribution costs, contribution margins, operating cash flows, asset productivity, and expected cash flows may affect valuation, impairment risk, covenant capacity, refinancing conditions, or financing capacity.
Distribution-Cost Transmission
The pathway through which computational demand leakage may increase reliance on paid and intermediated channels, raising acquisition and distribution costs.
Qualified-Demand Productivity Transmission
The pathway through which lower qualified-demand capture may affect occupancy, match velocity, time on market, time to transaction, and asset productivity.
Other Layers
Representation Layer
11 primitives
Agent-Readiness Layer
9 primitives
Global Market Layer
4 primitives
Governance Layer
9 primitives
Market Power Layer
6 primitives
Property Record Layer
14 primitives
Trade Infrastructure Layer
5 primitives
Measurement Layer
9 primitives
Discovery Layer
7 primitives
Economics Layer
8 primitives
Action Layer
1 primitives
Interoperability Layer
2 primitives