Affective Equity and Evidentiary Legibility: Testing Whether Brand Equity Predicts AI Citation or AI Recommendation
Timothy de Rosen, Paul Sheals · Zenodo (CERN European Organization for Nuclear Research) · 2026
AIVO's prior work (WP-2026-14, the Linkage Gap) established that AI systems cite a brand and then recommend a competitor 87.3 percent of the time across a corpus of more than 12,500 multi-turn purchase decision probes spanning 68 brands. That finding establishes that citation and recommendation are separable outcomes. It does not explain which brands are protected from displacement and which are not. This paper proposes that the explanation lies in a distinction between two forms of brand strength that are commonly treated as one. Affective Equity is the human-facing construct: sensory association, emotional memory, distinctive assets, and narrative resonance, the territory of classical brand equity theory. Evidentiary Legibility is the AI-facing construct: the density and structure of third-party-verifiable, attribute-level content available to an AI system evaluating a purchase decision. We hypothesize that Affective Equity predicts whether a brand is cited, consistent with recent third-party findings that long-term brand equity explains the majority of AI visibility, but that it does not predict whether a brand survives to become the final recommendation. We hypothesize that Evidentiary Legibility does predict survival, independent of Affective Equity, and that the Linkage Gap is concentrated among brands that are high on the former and low on the latter. We propose a method for testing this against AIVO's existing probe corpus and outline the construction of a new instrument, an Evidentiary Legibility score, required to run the analysis.