Cyber Insurance AI Visibility Ranking Trends - November 2026

Answer capsule

The November 2026 Cyber Insurance benchmark compares 10 companies across 239 AI answers that met its inclusion rules. Chubb leads with 68 recommendations (28.45% of answers). At least one tracked company was recommended in 74 answers; some answers recommended several companies.

The rankings distinguish being mentioned from receiving an affirmative recommendation, then examine placement and the wording used about each company. Earlier monthly results show how counts and rates changed, with each month using its own answer total. These results describe the answers reviewed, not product quality or customer satisfaction. Differences between monthly samples limit comparisons and do not establish why a result changed.

For the strategic interpretation of this benchmark, read CiteWorks Studio's analysis of How AI Search Is Recommending Cyber Insurance

Industry leaderboard

Questions This Section Answers

• How do Cyber Insurance rank by recorded AI recommendations in November 2026?

The leaderboard orders companies by how many answers affirmatively recommended them, not by how often they appeared. A company can be named frequently yet recommended rarely, so mention counts and recommendation counts answer different questions. Ties in recommendation counts would share a rank; the printed table shows the recorded ordering.

Placement figures are nested inside recommendations rather than separate wins. A first-place result is also a shortlist result, and both sit within the recommendation total. Reading the columns together shows how often appearances carry an endorsement and where endorsed companies tend to sit in an answer.

Key findings

Tracked-company answer coverage

Questions This Section Answers

• How often did the November 2026 Cyber Insurance answer sample recommend any tracked company?

74 distinct answers recommended at least one tracked company. Counting each company recommendation separately gives 229, because an answer can recommend several companies. Answers with no tracked recommendation may still have recommended companies outside this comparison.

Every included answer named at least one tracked company, but only a minority recommended one. Because a single answer can recommend several companies, the number of company-level recommendations exceeds the number of answers carrying any recommendation. These are overlapping appearances, not a market-share measure.

Answers without a tracked recommendation are not empty of advice; they may have named companies outside this comparison. Coverage therefore describes the reach of the tracked set within the reviewed answers, not the full range of options those answers offered.

Reach and affirmative recommendation

Chubb ranks 1 by recommendation count. Mentions: 207 (86.61%); recommendations: 68 (28.45%). Top 3 placements: 60 (25.10%); first-place placements: 42 (17.57%).

Wording about the company: 97 positive, 110 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 32.9%. The net framing score was 0.47 (defined in Methodology).

139 mentions had no recorded recommendation. Of recorded recommendations, 88.24% were Top 3 and 61.76% were first-place.

Chubb leads on recommendation count while Travelers appears in more answers, illustrating that reach and endorsement diverge. A mention records that a company appeared; a recommendation requires affirmative endorsement. Many mentions carried no recommendation, so presence alone should not be read as advocacy.

Where recommendation counts are equal, the companies share a position rather than one uniquely leading. The gap between mention totals and recommendation totals is the central distinction in this section, and it should be kept in view when comparing companies.

Recommendation order and placement

Placement describes where a recommended company sat in an answer's ordering. Shortlist and first-place counts are subsets of recommendations, so they should never be summed with recommendation totals or treated as extra endorsements. A company recommended less often can still place highly within the recommendations it received.

The recommendation-to-mention ratio compares endorsements with appearances in the recorded answers. It is not a conversion rate, a sales measure or evidence of customer preference. Where mention totals are small, a high ratio rests on a narrow base and should be read cautiously.

Classified framing in context

Framing classifies the wording used about a company in the answers where it appeared: positive, neutral or negative. It is not customer sentiment, reputation or a judgment of company quality. Neutral wording is common and does not imply criticism; it simply records descriptive rather than evaluative language.

Positive framing and affirmative recommendation are related but distinct. Wording can be favorable without a recommendation being recorded, and the reasons behind either are not established by these counts. Framing should be read alongside reach and recommendation, not as a substitute for them.

Company results in detail

Chubb

Questions This Section Answers

• What do the November 2026 AI answer results show about Chubb mentions, recommendations and placement?

Chubb ranks 1 by recommendation count. Mentions: 207 (86.61%); recommendations: 68 (28.45%). Top 3 placements: 60 (25.10%); first-place placements: 42 (17.57%).

Wording about the company: 97 positive, 110 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 32.9%. The net framing score was 0.47 (defined in Methodology).

139 mentions had no recorded recommendation. Of recorded recommendations, 88.24% were Top 3 and 61.76% were first-place.

From October 2026 to November 2026, Chubb's mention count rose from 161 to 207, while its recommendation count fell from 106 to 68. The recommendation rate was 63.10% and 28.45% respectively.

Chubb holds the top recommendation count and appears in most reviewed answers, giving it both broad reach and frequent endorsement. Its placements skew strongly toward the front of answers, with most of its recommendations landing in the top three and many in first place.

Framing is largely positive or neutral with no negative wording recorded. The month-over-month comparison shows mentions rising while recommendations fell, a divergence stated as recorded rather than explained; the samples differ between months.

Travelers

Questions This Section Answers

• What do the November 2026 AI answer results show about Travelers mentions, recommendations and placement?

Travelers ranks 2 by recommendation count. Mentions: 216 (90.38%); recommendations: 53 (22.18%). Top 3 placements: 39 (16.32%); first-place placements: 10 (4.18%).

Wording about the company: 84 positive, 132 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 24.5%. The net framing score was 0.39 (defined in Methodology).

163 mentions had no recorded recommendation. Of recorded recommendations, 73.58% were Top 3 and 18.87% were first-place.

From October 2026 to November 2026, Travelers' mention count rose from 154 to 216, while its recommendation count fell from 108 to 53. The recommendation rate was 64.29% and 22.18% respectively.

Travelers is named in more answers than any other tracked company, yet its recommendation count places it second behind Chubb. Its placements are more often shortlist than first-place, so endorsement is present but less often at the top of an answer.

Framing is predominantly neutral with a substantial positive share and no negative wording. Mentions rose while recommendations fell between the two months; that comparison is descriptive, and the differing samples do not establish a cause.

Hiscox Usa

Questions This Section Answers

• What do the November 2026 AI answer results show about Hiscox Usa mentions, recommendations and placement?

Hiscox Usa ranks 3 by recommendation count. Mentions: 58 (24.27%); recommendations: 30 (12.55%). Top 3 placements: 17 (7.11%); first-place placements: 8 (3.35%).

Wording about the company: 33 positive, 25 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 51.7%. The net framing score was 0.57 (defined in Methodology).

28 mentions had no recorded recommendation. Of recorded recommendations, 56.67% were Top 3 and 26.67% were first-place.

From October 2026 to November 2026, Hiscox Usa's mention count rose from 51 to 58, while its recommendation count fell from 45 to 30. The recommendation rate was 26.79% and 12.55% respectively.

Hiscox Usa reaches fewer answers than the largest names but is recommended in roughly half of the mentions it receives, a comparatively high recommendation-to-mention ratio. That ratio rests on a moderate mention base, so it should be read with that qualification in mind.

Its placements are frequently within the top three, and framing leans positive more than neutral with no negative wording. Mentions rose while recommendations fell across the two months, a recorded change whose cause is not established.

AIG

Questions This Section Answers

• What do the November 2026 AI answer results show about AIG mentions, recommendations and placement?

AIG ranks 4 by recommendation count. Mentions: 125 (52.30%); recommendations: 27 (11.30%). Top 3 placements: 8 (3.35%); first-place placements: 0 (0.00%).

Wording about the company: 45 positive, 80 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 21.6%. The net framing score was 0.36 (defined in Methodology).

98 mentions had no recorded recommendation. Of recorded recommendations, 29.63% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, AIG's mention count rose from 79 to 125, while its recommendation count fell from 46 to 27. The recommendation rate was 27.38% and 11.30% respectively.

AIG appears in a substantial share of answers but is recommended in a smaller fraction of them, so its reach exceeds its endorsement. Among its recommendations, shortlist placements occur while no first-place placements were recorded, meaning its endorsements rarely sat at the top of an answer.

Framing is mostly neutral with a positive minority and no negative wording. Mentions rose while recommendations fell between the months; the samples differ, so the comparison describes recorded results only.

Coalition

Questions This Section Answers

• What do the November 2026 AI answer results show about Coalition mentions, recommendations and placement?

Coalition ranks 5 by recommendation count. Mentions: 52 (21.76%); recommendations: 24 (10.04%). Top 3 placements: 17 (7.11%); first-place placements: 2 (0.84%).

Wording about the company: 28 positive, 24 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 46.2%. The net framing score was 0.54 (defined in Methodology).

28 mentions had no recorded recommendation. Of recorded recommendations, 70.83% were Top 3 and 8.33% were first-place.

From October 2026 to November 2026, Coalition's mention count stayed at 52, while its recommendation count fell from 42 to 24. The recommendation rate was 25.00% and 10.04% respectively.

Coalition receives a relatively high share of recommendations relative to its mentions, though on a smaller mention base than the leading insurers. Most of its recommendations are shortlist placements, with first-place appearances uncommon.

Framing is balanced between positive and neutral with no negative wording. Its mention count held steady across the two months while recommendations fell, so only one of the two measures was unchanged; the change is reported without an inferred cause.

CNA

Questions This Section Answers

• What do the November 2026 AI answer results show about CNA mentions, recommendations and placement?

CNA ranks 6 by recommendation count. Mentions: 53 (22.18%); recommendations: 9 (3.77%). Top 3 placements: 2 (0.84%); first-place placements: 0 (0.00%).

Wording about the company: 17 positive, 36 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 17.0%. The net framing score was 0.32 (defined in Methodology).

44 mentions had no recorded recommendation. Of recorded recommendations, 22.22% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, CNA's mention count rose from 41 to 53, while its recommendation count fell from 18 to 9. The recommendation rate was 10.71% and 3.77% respectively.

CNA is mentioned moderately often but recommended in a small fraction of those mentions, and its placements are rarely in the top three with no first-place results recorded. Endorsement is therefore limited relative to its visibility in the reviewed answers.

Framing is mostly neutral with a smaller positive share and no negative wording. Mentions rose while recommendations fell between the months; because the samples differ, this is a recorded comparison rather than evidence of a trend.

AXA XL

Questions This Section Answers

• What do the November 2026 AI answer results show about AXA XL mentions, recommendations and placement?

AXA XL ranks 7 by recommendation count. Mentions: 30 (12.55%); recommendations: 7 (2.93%). Top 3 placements: 4 (1.67%); first-place placements: 0 (0.00%).

Wording about the company: 11 positive, 19 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 23.3%. The net framing score was 0.37 (defined in Methodology).

23 mentions had no recorded recommendation. Of recorded recommendations, 57.14% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, AXA XL's mention count fell from 39 to 30, while its recommendation count fell from 25 to 7. The recommendation rate was 14.88% and 2.93% respectively.

AXA XL appears in a modest number of answers and is recommended in a smaller subset, with shortlist placements recorded and no first-place results. Its recommendation-to-mention ratio is moderate, resting on a limited mention base.

Framing is more neutral than positive with no negative wording. Both mentions and recommendations fell across the two months, a recorded change that the differing samples do not explain.

Beazley

Questions This Section Answers

• What do the November 2026 AI answer results show about Beazley mentions, recommendations and placement?

Beazley ranks 8 by recommendation count. Mentions: 31 (12.97%); recommendations: 6 (2.51%). Top 3 placements: 4 (1.67%); first-place placements: 0 (0.00%).

Wording about the company: 9 positive, 22 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 19.4%. The net framing score was 0.29 (defined in Methodology).

25 mentions had no recorded recommendation. Of recorded recommendations, 66.67% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, Beazley's mention count rose from 30 to 31, while its recommendation count fell from 18 to 6. The recommendation rate was 10.71% and 2.51% respectively.

Beazley's mentions are limited and its recommendations fewer still, with shortlist placements recorded and no first-place results. Its recommendation-to-mention ratio is modest, and the small base warrants caution in reading it as a stable pattern.

Framing is predominantly neutral with a small positive share and no negative wording. Mentions were nearly flat while recommendations fell between the months, so the two measures did not move together; the comparison is descriptive only.

At-Bay

Questions This Section Answers

• What do the November 2026 AI answer results show about At-Bay mentions, recommendations and placement?

At-Bay ranks 9 by recommendation count. Mentions: 27 (11.30%); recommendations: 4 (1.67%). Top 3 placements: 1 (0.42%); first-place placements: 0 (0.00%).

Wording about the company: 4 positive, 23 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 14.8%. The net framing score was 0.15 (defined in Methodology).

23 mentions had no recorded recommendation. Of recorded recommendations, 25.00% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, At-Bay's mention count rose from 24 to 27, while its recommendation count fell from 12 to 4. The recommendation rate was 7.14% and 1.67% respectively.

At-Bay is mentioned in a small share of answers and recommended in fewer, with a single shortlist placement and no first-place results recorded. Its recommendation-to-mention ratio is low, and the sparse base limits how firmly any pattern can be read.

Framing is overwhelmingly neutral with a small positive share and no negative wording. Mentions rose slightly while recommendations fell between the months; the differing samples do not establish why.

Cowbell Cyber

Questions This Section Answers

• What do the November 2026 AI answer results show about Cowbell Cyber mentions, recommendations and placement?

Cowbell Cyber ranks 10 by recommendation count. Mentions: 9 (3.77%); recommendations: 1 (0.42%). Top 3 placements: 1 (0.42%); first-place placements: 0 (0.00%).

Wording about the company: 1 positive, 8 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 11.1%. The net framing score was 0.11 (defined in Methodology).

8 mentions had no recorded recommendation. Of recorded recommendations, 100.00% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, Cowbell Cyber's mention count rose from 4 to 9, while its recommendation count fell from 3 to 1. The recommendation rate was 1.79% and 0.42% respectively.

Cowbell Cyber has the smallest footprint among the tracked companies, with few mentions and a single recorded recommendation, which was a shortlist placement. Ratios built on such a narrow base are unstable and should be treated as indicative only.

Framing is almost entirely neutral with one positive mention and no negative wording. Mentions rose while recommendations fell between the months, a recorded comparison whose cause is not established by these samples.

Earlier ranking snapshot context

Questions This Section Answers

• How do the available Cyber Insurance snapshots from July 2026 to November 2026 differ in recommendation coverage and measurement scope?

Only months with verified results are shown. Monthly sample coverage is listed in Methodology.

Each month is a separate sample of AI answers, and the number of included answers differs across months. Counts and rates therefore should be read against their own month's base rather than compared as if sampling were equivalent. Rank changes across months reflect those separate samples.

A shift in rank or rate between months does not demonstrate improvement, loss of standing or the effect of any intervention. The comparisons show how recorded results changed; they do not establish why.

What the November Rankings Show

The November results answer several distinct questions. Reach asks how often a company appeared; recommendation asks whether an answer affirmatively endorsed it; placement asks where an endorsed company sat in the ordering; framing asks how the wording was classified. A company can be strong on one and weak on another, which is why the leaderboard alone does not capture the full picture.

The gap between frequent mention and less frequent recommendation is the most consistent theme across the profiles. Placement figures are nested within recommendations, and framing is a separate classification of wording rather than a measure of sentiment or quality. Read together, these dimensions describe the reviewed answers without explaining why any company was or was not recommended.

Methodology

Questions This Section Answers

• How were the November 2026 Cyber Insurance AI visibility measures counted, and what do they not establish?

This benchmark has partial coverage: 1 of 3 planned question categories contributed usable observations; 2 contributed none. This describes question-category coverage, not demonstrated platform outages. Findings apply to the available answer set.

The month in the title is the reporting period. The exact dates when the original AI answers were collected have not been verified.

Each company is counted at most once in each answer that meets the benchmark rules. A recommendation requires both an affirmative endorsement and positive wording. Mention, recommendation, Top 3 and first-place rates use the full benchmark answer total. Top 3 and first-place results are included within recommendations, not added to them.

The recommendation-to-mention ratio divides recommendations by mentions. It describes AI answer wording, not customer conversion. Net framing is positive minus negative mentions, divided by all mentions, on a scale from -1 to +1. It does not measure customer satisfaction or company quality.

Market: US; 10 tracked companies. AI services represented: ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity.

Research screening totals (answer observations can include repeated questions):

The source does not provide a reader-facing definition of “reserved”; that screening label is reported without inferring a reason for exclusion. Only the included benchmark answers form the rate denominator.

One answer can mention or recommend several companies. Adding company totals would therefore count some answers more than once. The results describe the AI answers reviewed, not independently verified facts about the companies or their products.

Monthly sample coverage:

July 2026 measured a different set of companies, so it is excluded from this comparison. August 2026 measured a different set of companies, so it is excluded from this comparison.

The answer samples differ between months. These comparisons show how the recorded results changed; they do not establish why they changed.

Coverage is partial: only one of the planned question categories contributed usable answers, so findings apply to the available answer set rather than the full intended scope. The reporting month labels the period, but exact collection dates were not verified.

Each company is counted at most once per answer, and all rates use the full benchmark answer total. Top-three and first-place results sit inside recommendations, not alongside them. The recommendation-to-mention ratio and net framing describe answer wording, not customers, sales or company quality. Monthly samples differ, so comparisons show recorded change without establishing cause.