We ran the same structured prompt set against ChatGPT, Gemini, Perplexity, Copilot, and Claude, tracking every brand named or cited across 1,500 total responses and a verified universe of 137 insurance brands. The goal wasn't to find "the best AI for insurance" — it was to find out whether the five engines build visibility the same way. They don't.
Mention Volume Isn't Even Close
Total organic brand mentions varied substantially by engine: ChatGPT produced 1,171, Perplexity 925, Copilot 854, Claude 717, and Gemini 661 — a 1.8x spread between the highest and lowest engine. ChatGPT also named the most brands per response (3.9) in the shortest average answer (~205 words), while Perplexity wrote the longest answers (~648 words) naming fewer brands per response (3.1).
Citation Behavior Is Binary, Not Gradual
The starkest divide isn't volume — it's whether an engine cites sources at all. ChatGPT, Claude, and Gemini attached a source citation to 0.0% of their responses in this dataset; they name and recommend brands without a visible source trail. Perplexity cited a source in 100.0% of its responses, and Copilot in 95.7% — together, these two engines account for all 1,742 organic citations in the study.
| Engine | Organic mentions | Avg. length | Mentions/response | Citation rate | Top-3 rate |
|---|---|---|---|---|---|
| ChatGPT | 1,171 | ~205 words | 3.9 | 0.0% | 65.8% |
| Perplexity | 925 | ~648 words | 3.1 | 100.0% | 50.4% |
| Copilot | 854 | ~500 words | 2.9 | 95.7% | 65.6% |
| Claude | 717 | ~290 words | 2.4 | 0.0% | 55.5% |
| Gemini | 661 | ~398 words | 2.2 | 0.0% | 55.5% |
Source: Brainpan.AI Insurance AI Visibility Index™ — Q2 2026 benchmark, 137 brands, Finding 05 (Engine Divergence).
Five Operating Profiles
- ChatGPT — the shortest answers, the most brands named per response, and high Top-3 concentration (65.8%). A short, decisive, incumbent-favoring shortlist environment with zero visible citations.
- Perplexity — the longest responses and universal citation (100%) in the benchmark. It's also the only engine in the study where Progressive, not State Farm, leads outright.
- Copilot — long-form, near-universal citation (95.7%), and the highest Top-3 rate of the five (65.6%). The most structured, sourced, and decisive combination measured. Copilot is also the only engine where a paid layer appeared in this dataset: 224 paid mentions across 40 identified paid responses, all identified and excluded from organic scoring.
- Claude — moderate-length answers (~290 words) with fewer brand mentions per response (2.4) and no citations. A narrower visibility environment than ChatGPT.
- Gemini — longer than Claude but names the fewest brands per response (2.2) in the benchmark, with no citations.
The practical implication: there is no single "AI visibility score." A citation strategy is central to winning visibility on Perplexity and Copilot, but cannot explain outcomes on the three non-citing engines — there, the priority is inclusion, ordering, and recommendation strength instead.
Engine-by-Engine Optimization Priorities
Because Perplexity and Copilot reward live, citable content, brands under-indexed there benefit most from structured data, dated methodology pages, and digital-PR placement on the publisher domains those engines already trust. Brands under-indexed on the three non-citing engines (ChatGPT, Claude, Gemini) need to win on inclusion, prominence (Top-3 placement), and recommendation language instead — there is no citation lever to pull because none of the three attach visible sources.
Frequently Asked Questions
Do ChatGPT, Gemini, Perplexity, Copilot, and Claude cite the same brands?
Not consistently. Across our 137-brand study, total organic mentions ranged from 1,171 on ChatGPT down to 661 on Gemini — a 1.8x spread — and only Perplexity and Copilot supplied a source citation for the claims they made. ChatGPT, Claude, and Gemini named brands without citing sources at all in this dataset.
Which AI engine is most important to optimize for?
There isn't one universal answer — it depends on which engines your buyers actually use. Retrieval-first engines like Perplexity and Copilot reward structured, citable content; non-citing engines like ChatGPT, Claude, and Gemini reward being named, positioned prominently, and actively recommended, since they carry no visible source trail at all.
What does it mean when Perplexity cites a source without naming the brand?
It means the engine pulled content from that brand's domain as supporting evidence but didn't surface the brand name in the visible answer text. Every confirmed case of this pattern in our study came from Perplexity — 21 instances where a citation appeared without the underlying brand being named.
Is a five-engine study necessary, or does one AI engine represent the rest?
Given that three of the five engines measured here (ChatGPT, Claude, Gemini) cite zero sources while the other two (Perplexity, Copilot) cite almost every claim, a single-engine benchmark cannot represent the other four. A brand's citation strategy and its non-citing recommendation strategy are different disciplines entirely.
How often should cross-engine AI visibility be re-benchmarked?
Quarterly, at minimum, which is the cadence Brainpan.AI uses for the AIVI™ Insurance Benchmark. Engine retrieval behavior and training-data currency shift over time, and a benchmark run once cannot detect whether an optimization effort on one engine is working, stalling, or being offset elsewhere.
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Kevin Walsh
Kevin Walsh is the founder of Brainpan.AI, where he builds AI visibility infrastructure, GEO/AEO strategy, schema systems, and citation optimization programs for brands that need to be retrieved, cited, and trusted by AI answer engines.