Gemini is operated by Google. Gemini draws on Google's index plus a curated knowledge graph. It tends to weight Knowledge Graph entities and authoritative publishers more heavily than ChatGPT does, and is more cautious with named recommendations.
A law firm is discoverable inside Gemini if, when a prospect asks the platform a high-intent question, the firm is one of the named candidates the platform returns — with a positive rationale and an accurate description.
That's a higher bar than appearing in search results. Gemini answers are often more cautious — fewer named recommendations, more category-level guidance unless the entity is well established. Most lawyers have never measured whether they clear that bar. The AI Discovery Audit™ measures it, against an industry-comparable benchmark, on a 0–1000 scale.
"recommend a law firm in Sydney"
"recommend a law firm in Melbourne"
Plus 30+ vertical-specific variants per market.
Gemini draws on Google's index plus a curated knowledge graph. It tends to weight Knowledge Graph entities and authoritative publishers more heavily than ChatGPT does, and is more cautious with named recommendations.
For lawyers specifically, this means Knowledge Graph entity health, Wikipedia / Wikidata presence, schema.org alignment, and publisher citations carry disproportionate weight in whether your firm gets named when a prospect asks Gemini for a recommendation.
The law firms that win named recommendations on Gemini share four characteristics:
Across the Lawyers cohort we audit, the failure modes that most often suppress Gemini visibility are: no Wikidata entity; inconsistent business names across Google properties; entity dilution when sub-brands compete with the parent.
Each of these is fixable. None of them is fixed by buying more ads or more backlinks. They require structured remediation against a published methodology — which is what The Standard™ codifies and what the Audit measures against.
"The firms winning Gemini recommendations in 2026 are not the loudest. They are the ones with the cleanest signal."
The free Visibility Check produces a directional read in under five minutes. The full AI Discovery Audit™ — from $800, seven days — produces a complete 0–1000 scorecard with the eight-signal breakdown, including a platform-specific subscore for Gemini performance.
If you'd rather start with a conversation, the 30-minute call is free and produces a written summary of where you likely sit before any commitment.
Gemini answers are often more cautious — fewer named recommendations, more category-level guidance unless the entity is well established. So yes — though the format and consistency varies by platform and by query specificity.
Gemini draws on Google's index plus a curated knowledge graph. It tends to weight Knowledge Graph entities and authoritative publishers more heavily than ChatGPT does, and is more cautious with named recommendations. For this vertical specifically, the platform weights: Knowledge Graph entity health, Wikipedia / Wikidata presence, schema.org alignment, and publisher citations.
The common patterns we see: no Wikidata entity; inconsistent business names across Google properties; entity dilution when sub-brands compete with the parent. The AI Discovery Audit isolates which of these apply to your firm and quantifies the fix priority.
Not directly — there is no 'Gemini-only' optimisation. But the upstream signals that Gemini reads are addressable. That's what the AI Discovery Standard™ codifies, and what the Audit measures against.
The AI Discovery Audit™ delivers a 0–1000 score, an eight-signal breakdown, and a 90-day roadmap. From $800.
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