Where you stand in the AI answer layer.
Category intelligence on how brands are found, cited, ranked, and recommended across the AI answer layer — ChatGPT, Gemini, Perplexity, Copilot, and Claude — where buyers increasingly decide before they ever reach Google. Scored on the AIVI™ (AI Visibility Index), so you can see how you’re found today and fix it before a competitor becomes the default recommendation. Journalists and analysts: see the press and media kit.
Category-by-category research on how brands are found, cited, ranked, and recommended across ChatGPT, Gemini, Perplexity, Copilot, and Claude — scored with the AIVI™ (AI Visibility Index) and published as quarterly benchmark studies.
CMOs, brand and category leaders, and analytics teams who need an independent, methodology-backed read on where their brand stands in the AI answer layer — not a vendor's self-reported metric.
Start with the featured study for your category, then use the AIVI™ methodology section to understand how the score is built before comparing your brand's position against the named leaderboard.
Featured Study
— live nowQ2 2026 Insurance AI Visibility Benchmark
The first quarterly ranking of how leading insurance brands are found, cited, ranked, and recommended across the five major AI engines — the answer layer where buyers and agents now look before they ever reach Google or a broker. Built on organic placements only; paid is quarantined and reported separately. The leader sets the benchmark at 100 — and the drop-off is steep. Several recognizable carriers are invisible on at least one engine.
- 5 AI engines
- 134 insurance brands
- 1,500 responses
- 4,328 brand mentions
The full index — all 134 brands, per-engine detail — $3,500. One time payment. Single-organization commercial license.
The AIVI™ Index
— one weighted score for AI visibility (0–100)The Brainpan AIVI™ (AI Visibility Index) distils a brand's presence across five AI engines into a single, comparable 0–100 score. It is built on organic placements only — paid placements are quarantined and reported separately — and normalized so the category leader scores 100. The same five weighted components are measured identically on every engine, then re-run each quarter.
| Component | Weight | State Farm | Progressive | USAA | GEICO | Nationwide | Measured in |
|---|---|---|---|---|---|---|---|
| Share of Model | 35% | 457 | 308 | 270 | 265 | 252 | organic mentions |
| Recommendation strength | 25% | 705 | 471 | 521 | 405 | 416 | recommendation points |
| Position Weighting | 20% | 3.73 | 2.91 | 3.10 | 3.50 | 2.67 | average position |
| Citation Influence | 15% | 129 | 113 | 103 | 94 | 119 | citations (all sources) |
| Top-3 rate | 5% | 365 | 180 | 152 | 199 | 117 | top-3 finishes |
State Farm leads overall (AIVI™ 100.0), followed by Progressive (71.2), USAA (69.1), GEICO (65.6), and Nationwide (63.4). See the Top 10 named leaderboard →
AIVI™ Brand Score
The composite 0–100 score combining frequency and position to show true category leadership.
Share of Model
How often the AI names your brand in its answers — your share of all organic mentions in the category.
Recommendation strength
Whether the AI actively recommends you — not just mentions you — when asked to choose.
Position Weighting
Credit for landing first, not third — the top position in an AI answer is worth far more.
Citation Influence
Whether the AI attaches a source to your brand’s mention — a sourced mention still reaches the buyer, so all citations count. Citation Authority (third-party) is reported alongside.
Top-3 rate
How often your brand lands in the top three brands named within a single answer.
Methodology
— versioned, reproducible, organic-onlyStudy universe
134 approved brands and 300 stratified prompts spanning query types, funnel stages, and product lines — run across ChatGPT, Gemini, Claude, Perplexity, and Copilot for 1,500 total responses. The carrier universe is framed against the National Association of Insurance Commissioners record.
Organic basis
Paid ad-click placements are excluded from the index and disclosed in a separate supplement. A first-brand-mention rule prevents a single response from inflating any one brand.
Generative Engine Optimization
Prompts are designed around how buyers actually ask AI — by intent and funnel stage — so the index reflects real generative-engine behavior, not keyword proxies. The framing follows Aggarwal et al., GEO: Generative Engine Optimization (KDD 2024).
Technical infrastructure
Every citation URL is classified by origin — owned (1st-party), affiliated marketplace (2nd-party), and independent (3rd-party). The index counts all cited mentions as Citation Influence; Citation Authority (third-party) and Citation Independence (non-affiliated) are reported as companion metrics. Every ranking table is locked for reproducibility before publication, and the Q2 2026 results are published as open JSON, declared as schema.org Dataset resources under CC BY 4.0 — the Top 10 leaderboard, an OpenAPI description, and a per-brand record for every named insurer.
AIVI™ Methodology v1.0
The controlling document behind every published index: prompt-set construction, attribution rules, the five weighted components with their API field names, and the known limitations stated in full.
Read the methodology → AccountabilityCorrection policy
Any organization named in a published index can challenge a figure, client or not. Acknowledged in two business days, determined in ten, with declined requests logged alongside upheld ones.
Read the policy →Industry Benchmarks
— live now: InsuranceInsurance AI Visibility Benchmark
How 134 insurance brands are retrieved, cited, and recommended across the five major AI engines. Named rankings are live now.
View study → SeriesThe Insurance Benchmark Series
The evergreen home for every quarterly edition of the AIVI™ Insurance Benchmark — methodology, archives, and the latest results.
Explore the series →Latest Publications
— studies, editions, and analysisQ2 2026 Insurance Benchmark
Named top-brand rankings and headline findings — live now. Add your email and we'll send you the highlights.
Get the highlights → AnalysisIntroducing the AIVI™ Insurance Benchmark
Why insurance, what the AIVI™ score measures, and a first look at the shape of the leaderboard.
Read → SeriesAIVI™ Insurance Benchmark — Series Hub
Every edition of the benchmark in one place, with the methodology behind the index.
Explore → TeardownThe Hartford AI Visibility Teardown
The best top-three rate in the study and the worst recommendation rate. Six charts working through why one carrier ranks eighth.
Read the teardown → TeardownAllstate AI Visibility Teardown
The third-highest share of model in the study and sixth place on the index. Where 276 mentions stopped converting, and the 6.72 Visibility Points it cost.
Read the teardown → TeardownNationwide AI Visibility Teardown
Last in the published top ten on both placement measures, first on citation rate, and fifth overall. What a brand wins when it is sourced rather than positioned.
Read the teardown → MethodologyAIVI™ Methodology and Correction Policy
How the index is built, scored, and corrected — versioned, with the limitations and the challenge process stated on the record.
Read the document →
Kevin Walsh
Kevin Walsh is the founder of Brainpan.AI, where he builds the AI Visibility Engine, GEO/AEO strategy, schema systems, and citation optimization programs for brands that need to be retrieved, cited, and trusted by AI answer engines.
Request an AI Visibility Audit
See where your brand is visible, missing, or misrepresented across ChatGPT, Gemini, Perplexity, Copilot, Claude, and AI-powered search. Brainpan.AI will map the query targets, citation gaps, schema opportunities, and content changes needed to improve AI visibility. You'll receive a written audit document mapping your AI citation footprint, competitor gaps, and a prioritized 90-day roadmap — no sales call required before we start.