The AI Citation Gap: How Brand Demand, Authority, and Knowledge Panels Decide Which of 1,000 US Personal Injury Law Firms AI Assistants Cite

When a US consumer asks an AI assistant a legal question, the assistant answers with a synthesized paragraph and a short list of named entities and cited pages. Which law firms appear in those answers, and whose web pages host the citations, is rapidly becoming the discoverability question of the decade for the personal injury (PI) vertical, where a single signed case can be worth six or seven figures and a single head-term click transacts for hundreds of dollars. This paper is the eighth in a series on entity-completeness signals in the top-ranking US PI vertical. It presents, to our knowledge, the first large-N per-assistant AI citation audit of the vertical: for the same 1,000 top-ranking US personal injury law firm sample used throughout the series, we join per-firm mention and cited-page counts across four AI answer surfaces (ChatGPT, Gemini, Google AI Overview, and Google AI Mode) to the brand-search-demand, Person Entity Panel, Google Business Panel, domain-authority, and schema-completeness signals established in the prior papers. Three findings define what we name the AI Citation Gap. First, AI visibility is extremely concentrated: the median firm receives just 22 AI mentions across all four surfaces combined, the top 100 firms absorb 51.6% of all mentions, the bottom 500 firms share 9.6%, and the Gini coefficient of the mention distribution is 0.65. Second, the four assistants agree on who matters (pairwise Spearman rho = 0.70 to 0.88) but not symmetrically: 126 firms that are visible on Google's AI surfaces are completely absent from ChatGPT, while only 14 firms show the reverse pattern. Third, the citations are mostly not on the firm's own website. We introduce the Citation Intermediation Ratio (CIR), the share of a firm's AI citation footprint hosted by domains other than its own, and report a median CIR of 0.72: for the median firm, roughly 72% of its AI citations are hosted by third parties, with legal directories alone hosting 23%, and 99% of firms fall below 50% own-site share. Domain authority is the dominant correlate of AI mentions (rho = 0.80), brand search demand is the strongest firm-controllable second lever (firm brand rho = 0.44, significant in regression net of authority), the Person Entity Panel is citation-neutral, and the Google Business Panel is again associated with a citation deficit (median 19 vs 36 mentions, p < 0.001; OLS coefficient negative and significant), extending the zero-click cannibalization pattern documented in the Brand Demand Flywheel paper into the AI answer layer. An OLS model on log mentions reaches R-squared = 0.64. The paper closes with Citation Surface Optimization (CSO), a practitioner framework for managing owned versus rented AI citation surfaces.