A real Gap Report. Names hidden, findings intact.

1 · Executive summary

The practice achieves a 25/100 visibility score across four major AI recommendation engines, with presence in only one (Gemini) and exclusion from three (ChatGPT, Grok, Claude). The dominant gap is competitor dominance: named rivals — shown here as Competitors A–C — are systematically surfaced where the practice is not. This indicates the practice lacks the structured, citation-ready content and off-site authority signals that modern AI systems require to position it as a credible recommendation source.

2 · How the scan ran

Three high-intent buying prompts were tested across all four engines, each designed to capture buyer behaviour at the moment of provider selection:

• Best plastic surgery companies in Manhattan
• Who should I hire for plastic surgery services in Manhattan?
• Top recommended plastic surgery providers near Manhattan

Rather than guessing, we read the actual answer each engine returned and graded the practice 0–100 on visibility, recommendation status, and competitive positioning — recommended, mentioned, cited, displaced by a competitor, or excluded.

3 · AI recommendation coverage

The practice appears as a mentioned entity in only one of four engines (Gemini, 52/100) and is entirely excluded from three. Where it does appear, the reference is functional — a brief service mention — rather than a recommendation:

Across all engines, competitors receive named recommendations; the practice receives a functional mention at best.

4 · Citation coverage

The practice is not positioned as a primary recommendation source in any engine result. Where it is mentioned (Gemini), the citation lacks the evaluative language — "leading," "highly-regarded," "specialises in" — that signals trustworthiness to end users. This suggests the web presence does not currently provide the extractable, evaluative content that AI systems need to cite it with confidence.

5 · Competitor coverage

Across the four engines, a small set of named rivals is surfaced repeatedly in the practice's place:

All four engines prioritise named competitors over the practice. This pattern indicates that competing practices have stronger authority signals, more detailed web content, or higher third-party citation density.

6 · Authority gaps

The practice shows weak third-party endorsement signals. Competitors appear to benefit from a higher density of mentions in review platforms, medical directories, press coverage, and professional listings that AI engines draw on. Without comparable authority anchors, even excellent on-site content will struggle to compete for recommendation placement.

7 · Structure gaps

Content on the site likely lacks the semantic structure and extractable detail — credentials, specialties, patient outcomes, service descriptions — that modern AI systems require to parse and cite the practice as a credible source. Competitors' pages appear to present this information in ways that are more accessible to both AI indexing and direct user comprehension.

8 · Prompt-intent matrix

All three high-intent queries surface competitors. The practice's single appearance is in the broadest prompt, suggesting weak specialist positioning and low salience for decision-intent queries.

9 · Off-site authority snapshot

The practice does not appear to command the third-party mention density, review volume, or professional citations that would elevate it above competitors in AI results. This is an upstream visibility issue: without external authority signals, on-site optimisation alone will not move recommendation rankings.

10 · Priority fixes

Fix 1 · Structured content authority (critical). The service and credential pages lack the semantic, extractable information AI engines require to position the practice as a recommendation source. A Foundation Build systematically reconstructs content to include specialist credentials, service detail, patient outcomes, and comparative positioning — making the practice machine-readable and citation-ready across all four engines.

Fix 2 · Third-party citation density (critical). Competitors achieve placement partly through mentions in medical directories, review aggregators, and professional listings. A targeted authority program expands the practice's presence in the third-party sources these engines draw on, closing the citation gap that currently favours named rivals.

Fix 3 · Specialist positioning (high priority). The practice is not surfaced for decision-intent queries ("who should I hire," "top recommended"). Building explicit specialist positioning and a service-specific content hierarchy signals to AI systems that it should be ranked for high-intent searches, not just broad category queries.

11 · Final recommendation

The visibility gap reflects both on-site and off-site deficits. A Foundation Build is the appropriate entry point: it restructures the site to be AI-readable and establishes semantic clarity around credentials and specialties, preparing the practice to benefit from the authority-building work that follows. A Growth retainer then builds and sustains third-party citation density, working toward competitive parity with the rivals who currently dominate AI recommendation results.

AI visibility is measured through repeated prompt sampling and should be read directionally; month-to-month change can reflect optimisation work, competitor activity, or platform updates.