The Most-Cited Websites in AI for High-Stakes Insurance Consumer Decisions

LLM Authority Index Research | High-Stakes Consumer Decisions | Insurance | July-September 2026

Insurance is not one AI-search market.

A consumer comparing car insurance, Medicare supplement plans, life insurance, disability coverage, renters insurance, pet insurance, or travel insurance is making a high-stakes financial decision, but the websites AI systems visibly cite around those decisions can be radically different.

LLM Authority Index analyzed 14,360 deduplicated AI responses and 65,668 public-facing citation events across 12 insurance verticals and six AI platform families from July through September 2026.

At the overall category level, Forbes ranked #1, appearing as a cited domain in 18.9% of insurance responses, followed by NerdWallet at 17.0%, U.S. News at 13.4%, Money.com at 11.5%, and Reddit at 9.2%.

But the category-wide ranking hides commercially important specialization. Squaremouth appeared in 36.2% of Travel Insurance responses, Policygenius in 24.1% of Life Insurance responses, HealthcareInsider in 24.3% of Health Insurance responses, Pawlicy in 23.1% of Pet Insurance responses, and Insurify in 14.7% of Car Insurance responses.

That creates a useful distinction for insurance publishers and brands:

Broad insurance citation authority and vertical-specific citation authority are different commercial assets. A publisher can be a category-wide source across many insurance decisions, or it can dominate a narrower insurance vertical without appearing broadly across the rest of the category.

This study is part of the 2026 AI Citation Authority Study, which analyzes 278,499 citation events across the broader High-Stakes Consumer Decisions research panel.

Answer Capsule

Which websites are most frequently cited by AI for high-stakes insurance consumer decisions? In the LLM Authority Index July-September 2026 insurance panel, Forbes ranked #1, appearing in 18.9% of 14,360 deduplicated AI responses, followed by NerdWallet at 17.0%, U.S. News at 13.4%, Money.com at 11.5%, and Reddit at 9.2%. The Top 100 domains accounted for 65.9% of response-level domain appearances, and 87 domains remained in the insurance Top 100 across all three months. Platform differences were substantial: only 16 domains appeared in the insurance Top 100 for all six AI platform families.

Key Findings

• The source archive contains 14,818 raw July-September observations assigned to the Insurance family before analytical cleaning.
• 8 insurance observations, or approximately 0.05%, were explicitly marked as extraction failures and excluded from valid-response analysis.
• After exact repeated-record handling across overlapping vertical exports, the category contains 14,360 deduplicated AI responses.
• The public insurance ranking dataset contains 65,668 citation events after the infrastructure exclusions described in the methodology.
• Those responses cited approximately 3,663 registrable domains.
• Forbes ranked #1 with 2,716 responses citing the domain, or 18.9% category response coverage.
• NerdWallet ranked #2 at 17.0%, followed by U.S. News at 13.4%, Money.com at 11.5%, and Reddit at 9.2%.
• The Top 10 domains represented 26.5% of all response-level domain appearances in the category.
• The Top 25 represented 40.4%, the Top 50 represented 53.1%, and the Top 100 represented 65.9%.
• 87 domains appeared in the insurance Top 100 in July, August, and September.
• August and September shared 93 of 100 domains, producing 86.9% Jaccard similarity.
• Only 16 domains appeared in the insurance-specific Top 100 for all six platform families.
• Median pairwise Top 100 overlap between platforms was only 29.0%, substantially lower than the month-to-month overlap.
• Google AI Mode and Google AI Overviews had the most similar insurance Top 100 lists, sharing 87 domains, or 77.0% Jaccard similarity.
• Gemini and Microsoft Copilot had the least similar insurance Top 100 lists, sharing 30 domains, or 17.6% Jaccard similarity.
• Forbes and Money.com were cited in all 12 insurance verticals and across all six platform families in the measured panel.
• Money.com ranked #4 overall in insurance, with 11.5% response coverage across the category.
• Specialist insurance publishers were often much stronger inside a particular vertical than their category-wide rank suggests.

Questions This Study Answers

• Which publishers are most frequently cited when consumers ask AI systems about insurance?
• Which websites can demonstrate measurable AI citation visibility to insurance advertisers and carrier partners?
• Which publishers have citation visibility across the broadest range of insurance products?
• Which specialist publishers dominate individual verticals such as Travel Insurance, Life Insurance, Pet Insurance, Health Insurance, and Car Insurance?
• Should an insurance CMO use the same publisher outreach list for Google AI Overviews, Google AI Mode, and ChatGPT?
• Which third-party sources should insurance carriers, brokers, comparison sites, and agencies evaluate for AI-search earned media?
• Which insurance citation sources remain visible month after month?
• What websites are most visible in AI answers for Medicare Supplement, Renters Insurance, Disability Insurance, Dental Insurance, and the other verticals in this study?
• Can publishers use independent insurance citation data in advertiser pitches without claiming that publishing on the site causes AI recommendations?
• How concentrated is visible AI citation authority in insurance?

Why This Research Belongs in Daily AI Search Marketing Decisions

This study is research-based, but its purpose is commercial decision support.

Insurance marketers operate in a source market where broad category authority and narrow product authority can both matter. Forbes can lead the full insurance category while Squaremouth is far more important in Travel Insurance, Policygenius is disproportionately important in Life Insurance, Pawlicy is unusually strong in Pet Insurance, and HealthcareInsider is more relevant inside Health Insurance than its category-wide position alone would suggest.

For publishers, that creates a measurable commercial asset: AI citation visibility can be documented by category, product vertical, platform, and time rather than reduced to pageviews or one blended SEO metric.

For insurance carriers, brokers, agencies, comparison sites, and CMOs, the same research answers a different operating question:

Which sources are already present around the high-value insurance decisions our customers are asking AI systems to help them make?

The insurance family also provides one of the clearest examples of the Persistence-Portability Gap.

• Concentration: the category Top 100 accounted for 65.9% of response-level domain appearances.
• Persistence: the median of the three reported monthly Top 100 Jaccard comparisons was 80.2%.
• Portability: the median pairwise Jaccard similarity across the six platform-specific insurance Top 100 lists was 29.0%.

Using the same summary-based operationalization described in Article 01, those displayed values produce an approximate 51.2 percentage-point Persistence-Portability Gap for insurance.

That category-level gap is exploratory. It is calculated from published summary statistics, not from a newly reconciled raw-data rebuild or controlled platform-by-month experiment.

The commercial meaning is still important: insurance source authority was highly persistent over time but much less transferable across AI platforms. A publisher list that is strategically useful for one platform can be incomplete for another even when the category's leading domains barely change month to month.

The parent insurance analysis reports 16 domains in the category-specific Top 100 across all six AI platform families. At the same time, the weakest platform pair shared only 30 of 100 domains, or 17.6% Jaccard similarity.

That supports a three-tier operating model:

1. Cross-platform insurance core: broad sources that repeatedly matter across several engines and multiple insurance products.
2. Platform-specific source layer: publishers and institutions that matter disproportionately on ChatGPT, Google AI Search, Gemini, Perplexity, or Copilot.
3. Product-specific specialist layer: sources that can dominate Travel, Life, Pet, Health, Auto, Medicare Supplement, Renters, Disability, or another insurance decision without being category-wide leaders.

Commercial Action Matrix: What Publishers and CMOs Can Do With the Findings

The daily operating implication is straightforward: insurance AI search marketing should combine a durable category source map with platform-specific and product-specific source maps.

Citation visibility is evidence of source presence, not proof that a publication, relationship or placement causes an AI system to recommend an insurer or policy.

How This Study Fits the High-Stakes Consumer Decisions Research Corpus

Article 06 is the category parent for Insurance research in the LLM Authority Index High-Stakes Consumer Decisions series.

The surrounding studies answer different commercial questions:

• The 2026 AI Citation Authority Study establishes the full high-stakes source layer and compares concentration, persistence and portability across the four decision families.
• The Persistence-Portability Gap provides the measurement language for separating temporal durability from cross-platform source-set transferability.
• Do AI Platforms Cite the Same Websites? provides the overall portability context.
• How Stable Are AI Citations? provides the overall persistence and same-prompt drift context.
• Reddit's Decline in AI Citations shows how one major source can move inside a relatively persistent aggregate market.
• Reddit's Decline in AI Citations for Insurance isolates that trend inside this decision family.
• Articles 18, 19, 20, 34, 35 and 36 are the six platform-specific Insurance source studies.
• Articles 46, 47, 48, 58, 59 and 60 are the six platform-specific Insurance Reddit trend studies.

Article 06 should therefore function as the Insurance category hub. It identifies the broad source ecosystem and product-level specialists. The platform studies show where that source market changes by engine. The longitudinal studies show which source relationships persist or decline over time.

What We Studied

The Insurance family contains 12 source vertical labels from the broader LLM Authority Index High-Stakes Consumer Decisions panel:

1. Car Insurance
2. Dental Insurance
3. Disability Insurance
4. Health Insurance
5. Life Insurance Companies
6. Long-Term Care Insurance
7. Medicare Supplement Insurance
8. Pet Insurance
9. Renters Insurance
10. Short Term Health Insurance
11. Travel Insurance
12. Vision Insurance

The six public AI platform families are:

• Google AI Overviews
• Google AI Mode
• ChatGPT
• Gemini
• Perplexity
• Microsoft Copilot

Category analysis size

Responses by month

Responses by platform family

Different platform families expose different numbers of citations per response, so these raw response and citation totals should not be interpreted as platform market share. The primary ranking metric is response-level domain presence within the measured insurance panel.

The Most-Cited Websites in AI for Insurance Decisions

Response citation coverage measures the percentage of deduplicated insurance responses in which a registrable domain appeared at least once. A domain counts no more than once per response for this metric, even when several URLs from the same site were cited.

Top 25 insurance citation sources

The ranking contains several different source types: broad publishers, insurance comparison sites, carrier-owned domains, government resources, community sites, and specialist publishers. A later source-type study will separate first-party and third-party sources more formally.

The Full Top 100 Insurance Citation Sources

Downloadable dataset placeholder: {INSURANCE_TOP100_CSV_URL}

The Most-Cited Sources by Individual Insurance Vertical

Publishing one article for every individual insurance vertical would create a large number of thin pages that repeat the same methodology. Instead, this category study keeps the evidence centralized and gives each vertical a direct answer inside one substantive research page.

The percentages below are response-level coverage within the named vertical. Multiple domains can appear in the same response, so the percentages are non-exclusive and do not sum to 100%.

Three patterns are worth highlighting.

Broad publishers can still dominate narrow insurance decisions

Forbes leads the overall insurance category and also ranks among the leading sources in Dental Insurance, Health Insurance, Pet Insurance, Short Term Health Insurance, Vision Insurance, and several other verticals.

NerdWallet ranks #2 overall and leads Disability Insurance, Medicare Supplement Insurance, and Renters Insurance in this panel.

Specialist publishers can be disproportionately important

Squaremouth is only #9 in the category-wide ranking and appears in two of the 12 insurance verticals, but it is cited in 36.2% of Travel Insurance responses, the highest response coverage of any leading domain in the vertical table.

Pawlicy appears in only one category vertical but reaches 23.1% of Pet Insurance responses.

Policygenius reaches 24.1% of Life Insurance responses, while HealthcareInsider reaches 24.3% of Health Insurance responses.

That distinction matters commercially. A publisher with narrow but intense vertical authority can be more relevant to an advertiser than a broader site with lower presence in that exact product category.

Government and first-party sources matter in selected verticals

medicare.gov reaches 14.5% response coverage in Medicare Supplement Insurance. Carrier and provider domains such as geico.com, humana.com, uhc.com, vsp.com, allstate.com, and progressive.com also appear among the leaders in individual verticals.

The insurance source ecosystem is therefore not simply a contest among editorial publishers.

Which Websites Have the Broadest Insurance Vertical Coverage?

A separate commercial question is breadth: how many of the 12 insurance verticals cite a domain at least once?

Forbes and Money.com combine both breadth and cross-platform reach in this panel: each appears in all 12 insurance verticals and all six AI platform families.

ValuePenguin also appears in all 12 verticals and all six platform families, though at lower overall response coverage.

For advertisers, this kind of breadth can matter when a campaign spans multiple insurance products. For specialist campaigns, vertical concentration may matter more.

The Top Insurance Sources Differ Materially by AI Platform

Only 16 domains appeared in the insurance Top 100 for all six platform families:

anthem.com, deltadental.com, forbes.com, humana.com, insurance.com, insuranceopedia.com, insure.com, insurify.com, lendingtree.com, medicareguide.com, money.com, moneygeek.com, policygenius.com, squaremouth.com, uhc.com, and valuepenguin.com.

The median pairwise overlap between platform-specific insurance Top 100 lists was only 29.0% by Jaccard similarity.

Top five insurance sources by platform

Several commercial differences are immediately visible:

• Google AI Overviews begins with NerdWallet, U.S. News, Forbes, Reddit, and Money.com.
• Google AI Mode begins with U.S. News, NerdWallet, Forbes, Money.com, and Reddit.
• ChatGPT is much more concentrated at the top in this dataset, with Forbes appearing in 48.35% of insurance responses captured for that platform family.
• Gemini puts Money.com first in the insurance category.
• Microsoft Copilot begins with Forbes, U.S. News, NerdWallet, MoneyGeek, and Money.com.
• Perplexity begins with NerdWallet, Forbes, and Money.com.

This reinforces the broader finding from Do AI Platforms Cite the Same Websites for High-Stakes Consumer Decisions?: a publisher strategy that is strong for one AI platform should not automatically be treated as optimal for another.

Reserved platform-study links:

• The 100 Most-Cited Websites in Google AI Overviews for High-Stakes Insurance Consumer Decisions
• The 100 Most-Cited Websites in Google AI Mode for High-Stakes Insurance Consumer Decisions
• The 100 Most-Cited Websites in ChatGPT for High-Stakes Insurance Consumer Decisions
• The 100 Most-Cited Websites in Perplexity for High-Stakes Insurance Consumer Decisions
• The 100 Most-Cited Websites in Gemini for High-Stakes Insurance Consumer Decisions
• The 100 Most-Cited Websites in Microsoft Copilot for High-Stakes Insurance Consumer Decisions

Insurance Citation Authority Was More Stable Over Time Than Across Platforms

The insurance Top 100 changed relatively little from month to month.

Across all three months, 87 domains remained in the insurance Top 100.

The category leaders were also stable:

• Forbes ranked #1 in July, August, and September.
• NerdWallet ranked #2 in all three months.
• U.S. News ranked #3 in all three months.
• Money.com moved from #5 in July to #4 in August and September.
• Reddit moved from #4 in July to #5 in August and September.

Compare that persistence with the platform-specific fragmentation. Google AI Mode and Google AI Overviews shared 87 of their insurance Top 100 domains, but the weakest platform pair shared only 30.

This is another example of the study-wide pattern documented in How Stable Are AI Citations for High-Stakes Consumer Decisions?: the publisher portfolio can be relatively stable over time while still differing materially by platform and by individual query.

What the Results Mean for Insurance Publishers

Publishers can use citation research responsibly as independent evidence of visibility.

A broad publisher may be able to document:

• citation visibility across multiple insurance verticals;
• visibility across multiple AI platform families;
• persistence over several months;
• strength inside one or more commercially valuable insurance subcategories; and
• relative position versus other publishers in the same measured panel.

A specialist publisher can make a different case.

Squaremouth does not need to be a Top 5 category-wide insurance domain to demonstrate commercial relevance. Its 36.2% response coverage in Travel Insurance is a more specific and potentially more useful statistic for a travel-insurance advertiser.

Likewise, Pawlicy can point to Pet Insurance rather than broad insurance, and Policygenius can point to Life Insurance rather than needing to dominate every insurance vertical.

The defensible claim is:

Our domain is measurably present among the sources AI platforms cite when consumers research this insurance category.

The unsupported claim would be:

Publishing with us will cause AI systems to recommend your brand.

This study supports the first statement, not the second.

What the Results Mean for Insurance CMOs, Carriers and Brokers

Insurance marketers should avoid treating the overall Top 100 as a single universal outreach list.

A more useful workflow is:

1. identify the exact insurance verticals tied to the business;
2. identify the publishers and first-party sources most visible inside those verticals;
3. separate broad multi-vertical publishers from specialists;
4. compare the source set across Google AI Overviews, Google AI Mode, ChatGPT, and other priority platforms;
5. track whether the relevant domains persist over time; and
6. investigate which pages, data assets, comparisons, reviews, tools, and third-party citations are actually earning visibility.

For example, a Life Insurance strategy should pay close attention to Policygenius, NerdWallet, Ethos, U.S. News, and Money.com in this dataset. A Travel Insurance strategy should focus much more heavily on Squaremouth, U.S. News, NerdWallet, Forbes, and InsureMyTrip.

The category title is the same. The publisher market is not.

Reddit in Insurance AI Citations

Reddit ranks #5 overall in the three-month insurance category, with 9.2% response coverage across the full measured panel, but its broader citation presence declined materially from July to September in the overall High-Stakes Consumer Decisions study.

Because that movement can be hidden inside a three-month aggregate, LLM Authority Index is publishing a separate longitudinal insurance analysis:

Reddit's Decline in AI Citations for High-Stakes Insurance Consumer Decisions

The broader cross-category study is available at Reddit's Decline in AI Citations: What Changed Across High-Stakes Consumer Decisions From July to September 2026?.

How This Study Relates to Prior Insurance AI Research

Insurance already has meaningful AI-search research. This study should be evaluated against that work rather than presented as if the field were empty.

Conductor: 3.6 Million Insurance Brand Citations Across Seven Engines

Conductor's 2026 Insurance AI Search & AI Overviews Benchmarks analyzes more than 3.6 million insurance brand citations from January through May 2026 across seven answer engines and more than 178,000 prompts. Its answer-engine analysis covers 445 insurance domains and reports Insureon, Progressive, The Hartford, New York Life, and Chubb as the leading insurance domains by AI citation market share. (Conductor insurance benchmarks)

That is important prior art, and its dataset is far larger than the LLM Authority Index insurance slice.

The measurement population is also different.

Conductor classifies a citation into Insurance based on the industry of the domain being cited. Its published leaders are therefore insurance carriers, brokers, and insurance-industry domains competing for citation market share.

LLM Authority Index begins with the consumer decision prompt family and then counts all visible source domains cited in those responses. That means broad publishers such as Forbes, NerdWallet, U.S. News, Money.com, Reddit, and Investopedia remain in scope alongside carriers, government sources, brokers, comparison sites, and specialists.

This explains why the leading domains differ without implying that either study is wrong.

Temso: More Than 220,000 Insurance Source Citations Across Models and Markets

Temso analyzed more than 220,000 AI source citations across 22,063 insurance-related responses from ChatGPT, Microsoft Copilot, Grok and Google AI Overview across 12 countries and seven languages during Q2 2026. Its prompts include choosing, comparing and recommending car, home, health and life insurance, brokers and comparison platforms.

Source: Temso, "Which Websites Shape AI Answers About Insurance?"

Temso's cross-model result is especially relevant to the portability finding in this article. Across its model pairs, the average overlap among the Top 20 cited domains was 26.4%, meaning roughly 73.6% of top sources differed between a typical pair.

That is directionally consistent with the platform fragmentation measured here, where the median pairwise overlap among insurance Top 100 lists is 29.0%.

The percentages should not be treated as interchangeable. Temso uses Top 20 lists, four models, multinational and multilingual insurance prompts, and citation-share rankings. LLM Authority Index uses Top 100 response-coverage lists across six public platform families in a U.S.-oriented high-stakes commercial research corpus.

The important agreement is structural: insurance source authority is highly model-specific even when every platform is answering insurance questions.

Tinuiti and Profound: Multi-Platform Commercial Citation Tracking

Tinuiti's Q3 2026 AI Citation Trends Report tracks ChatGPT, Perplexity, Google AI Mode, Google AI Overviews, Gemini and Microsoft Copilot across commercial prompt categories. Insurance is not one of the report's tracked categories, so its figures should not be imported into this insurance ranking.

Source: Tinuiti, "AI Citation Trends Report Q3 2026"

Its relevance is methodological and commercial. Tinuiti reports source-type and platform shifts over time and shows why a marketer should not assume that citation behavior is fixed across engines or quarters.

Tinuiti has also warned across its citation research that platforms can emit very different numbers of citations per response. LLM Authority Index addresses that same cross-platform comparability problem by using response-level domain presence as the primary ranking metric rather than treating raw citation-event totals as normalized market share.

BrightEdge: High-Stakes Categories Can Have Different Authority Structures by Platform

BrightEdge compared citation presence in healthcare and finance between ChatGPT and Google AI Overviews and found materially different source structures between the two platforms. In healthcare, ChatGPT's leading sources were predominantly government and hospital domains, while Google AI Overviews showed a different pattern that included strong YouTube visibility. (BrightEdge high-stakes citation research)

Insurance is a different category, but the methodological lesson is relevant: authority should be measured within the platform and category rather than assumed from a general web ranking.

How the LLM Authority Index Insurance Study Is Different

The distinguishing feature of this article is not size. Conductor's insurance dataset is much larger, and Temso also has a substantial insurance-specific source corpus.

The LLMAI contribution is the combination of the following elements:

High-stakes consumer decision framing

The unit of interest is the consumer insurance decision, not simply whether a cited domain belongs to the insurance industry.

All visible source types remain in scope

Independent publishers, insurance specialists, carriers, government sites, nonprofits, communities, platforms, and other cited domains can all appear in the same ranking.

Twelve distinct insurance verticals

The category includes Car, Dental, Disability, Health, Life, Long-Term Care, Medicare Supplement, Pet, Renters, Short Term Health, Travel, and Vision Insurance.

Six public AI platform families

Google AI Overviews, Google AI Mode, ChatGPT, Gemini, Perplexity, and Microsoft Copilot are evaluated under one analytical framework.

Three-month longitudinal structure

July, August, and September are preserved separately so category authority can be distinguished from one-month movement.

Response-level domain coverage

A domain is counted once per response for the primary ranking, reducing the impact of platforms that emit many citation URLs in one answer.

Exact repeated-record handling across overlapping exports

The same prompt and identical citation set appearing in overlapping vertical exports is counted once in the category-wide structural analysis.

Why Insurance AI Citation Studies Can Produce Very Different Rankings

Insurance is a particularly good example of why citation studies can disagree while all of them remain internally valid.

The ranking can change based on:

• whether the study begins with insurance prompts or insurance-domain classification;
• whether broad publishers are allowed to compete with insurance companies;
• which insurance products are included;
• whether commercial, informational, or brand prompts dominate the sample;
• country and language;
• platform mix;
• collection dates;
• whether raw citation events or response-level presence is the denominator;
• whether subdomains are consolidated;
• treatment of platform-owned surfaces and infrastructure links; and
• whether a study measures citations, company mentions, recommendations, or all three.

For example, Conductor's finding that the leading insurance-brand domains hold roughly similar low-single-digit citation market shares is not directly comparable with Forbes appearing in 18.9% of LLMAI insurance responses. One measures market share among a defined insurance-domain universe, while the other measures response-level presence among all source domains cited in a high-stakes insurance prompt panel.

They answer different questions.

Methodology

Research source

This category study uses the same frozen source archive as the 2026 AI Citation Authority Study.

The broader parent analysis contains 60,881 deduplicated AI responses and 278,499 visible citation events across July, August, and September 2026.

Insurance family assignment

The 12 source vertical labels listed above are assigned to the Insurance family for category-level analysis.

These labels are treated as source memberships, not as proof that every prompt is perfectly classified. Prompt-level review is still required for narrower causal or vertical-specific claims.

Explicit extraction failures

The delivered July-September insurance source files contain 8 observations explicitly marked as extraction failures. Those observations are excluded from valid-response analysis rather than treated as ordinary zero-citation responses.

Exact repeated-record handling

Overlapping vertical exports can contain the same observed prompt and citation set.

For category-wide structural analysis, a record is counted once when all of the following match:

1. report month;
2. exact raw source surface;
3. normalized prompt text; and
4. exact set of original citation URLs.

All originating vertical memberships are preserved on the surviving analytical record.

Prompt normalization

Prompt matching uses Unicode NFKC normalization, case folding, whitespace collapse, and trimming. Wording is otherwise preserved.

Registrable-domain normalization

Citation URLs are parsed to hostnames and consolidated to the registrable domain using the Public Suffix List.

This prevents subdomains such as a finance or insurance subdomain from being counted as separate publishers when they belong to the same registrable domain.

Infrastructure exclusions

Obvious non-substantive technical assets and navigation wrappers are excluded from the public ranking, including known image hosts, map or ad wrappers, account-activity pages, and CloudFront asset hosts.

Platform-owned substantive surfaces are not automatically excluded simply because the platform owns the domain.

Primary ranking metric

The primary metric is response citation coverage:

response citation coverage = deduplicated insurance responses citing domain / all eligible deduplicated insurance responses

A domain counts no more than once per response for this metric.

Raw citation events

Citation-event totals are also reported as a secondary metric. If one response cites several URLs from the same domain, those can contribute several citation events even though the domain receives only one response-level appearance.

Monthly Top 100 overlap

Monthly Top 100 sets are constructed independently using response-level domain presence. Pairwise overlap uses Jaccard similarity:

Jaccard similarity = shared domains / unique domains across both lists

Platform Top 100 overlap

Each public platform family receives its own category Top 100. The intersection and pairwise Jaccard values are then calculated across the six lists.

Vertical-level rankings

For the 12 vertical rows, every category record retains its originating vertical memberships. Response-level domain coverage is then calculated within each vertical membership set.

Because overlapping vertical records can share a common analytical record, vertical sample sizes should not be summed and treated as independent category observations.

Missing months

Long-Term Care Insurance, Renters Insurance, and Vision Insurance were not produced in July in the preserved archive. Missing months are treated as unavailable, not as zeros and not as extraction failures.

No missing month is imputed.

Limitations

1. This study measures visible citations, not hidden retrieval, training data, or internal model reasoning.
2. Citation is not endorsement. A platform can cite a domain while disagreeing with it or recommending another company.
3. Citation is not causation. The data does not prove that publication on a cited site causes a company to be mentioned or recommended.
4. Insurance verticals differ greatly in sample size. Long-Term Care Insurance has a much smaller usable panel than Travel Insurance or Dental Insurance.
5. Three verticals have no July dataset in the preserved source archive. Missing months are not zero-filled.
6. The platform families are not sampled in identical quantities. Cross-platform raw citation totals should not be interpreted as market share.
7. Platform citation surfaces differ technically. A citation captured from one platform is not necessarily exposed in the same way on another.
8. Some source datasets can contain adjacent or imperfectly routed prompts. The category is appropriate for broad insurance analysis, but narrow vertical claims require prompt-level review.
9. Registrable-domain consolidation can hide page-level differences. Two citations to different sections of the same publisher count under one domain.
10. The July-September window is observational and time-specific. Rankings can change as models, indexes, products, and publisher content change.
11. This is a high-stakes commercial panel, not a representative sample of every insurance question consumers ask.

Commercial Relationship Disclosure

LLM Authority Index is part of a business ecosystem that provides AI visibility, research, and marketing services. Affiliated businesses may have current or historical commercial relationships with companies or publishers that appear in the dataset, including publishers that rank in this article.

Commercial relationships are not inputs to the ranking methodology. Domains are included and ranked based on observed citation data under the published rules. No ranking position should be interpreted as an endorsement, and no commercial relationship should be interpreted as evidence that the relationship caused citation visibility.

References

1. LLM Authority Index. The 2026 AI Citation Authority Study.
2. LLM Authority Index. The Persistence-Portability Gap.
3. LLM Authority Index. Do AI Platforms Cite the Same Websites for High-Stakes Consumer Decisions?.
4. LLM Authority Index. How Stable Are AI Citations for High-Stakes Consumer Decisions?.
5. LLM Authority Index. Reddit's Decline in AI Citations Across High-Stakes Consumer Decisions.
6. LLM Authority Index. Reddit's Decline in AI Citations for Insurance.
7. Conductor. 2026 Insurance AI Search & AI Overviews Benchmarks.
8. Temso AI. Which Websites Shape AI Answers About Insurance?.
9. Tinuiti. AI Citation Trends Report Q3 2026.
10. BrightEdge. Institution or Platform: What Health and Finance Citations Reveal About ChatGPT and Google AI Overviews.

Related LLM Authority Index Research

Foundation and measurement framework

• The 2026 AI Citation Authority Study
• The Persistence-Portability Gap
• Do AI Platforms Cite the Same Websites?
• How Stable Are AI Citations?
• Reddit's Decline in AI Citations Across High-Stakes Consumer Decisions

Insurance platform source studies

• Google AI Overviews Insurance source study

• Google AI Mode Insurance source study

• ChatGPT Insurance source study

• Perplexity Insurance source study

• Gemini Insurance source study

• Microsoft Copilot Insurance source study

Insurance Reddit trend studies

• Insurance Reddit parent study
• Google AI Overviews Reddit trend study
• Google AI Mode Reddit trend study
• ChatGPT Reddit trend study
• Perplexity Reddit trend study
• Gemini Reddit trend study
• Microsoft Copilot Reddit trend study

Sibling decision-family studies

• Credit, Debt, Banking and Lending source study
• Investing, Retirement, Mortgage and Financial source study
• Health and Medical source study

The Insurance category study is the hub for the product-level and platform-level branch. The source studies answer which domains recur most often on each engine. The Reddit trend studies answer how one important source changed over time inside those engines.