Life Insurance Companies AI Visibility Ranking Trends - November 2026

Answer capsule

The November 2026 Life Insurance Companies benchmark compares 6 companies across 318 AI answers that met its inclusion rules. Ethos leads with 207 recommendations (65.09% of answers). At least one tracked company was recommended in 261 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 Life Insurance Companies

Industry leaderboard

Questions This Section Answers

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

The leaderboard orders companies by how many answers affirmatively recommended them. That count is not the same as appearing in an answer, and it is not the same as being placed near the top of a list. A company can be mentioned often yet recommended less often, so the columns answer different questions.

Ties are possible when recommendation counts are equal; equal counts do not establish a unique winner. Placement figures are nested inside recommendations rather than added to them. Reading mentions, recommendations and placements separately keeps each measure in its own lane.

Key findings

Tracked-company answer coverage

Questions This Section Answers

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

261 distinct answers recommended at least one tracked company. Counting each company recommendation separately gives 597, because an answer can recommend several companies. Answers with no tracked recommendation may still have recommended companies outside this comparison.

Every qualified answer mentioned at least one tracked company, but recommendation coverage was narrower: most answers recommended at least one tracked company, while a smaller group recommended none. Many answers recommended more than one company, which is why company-level recommendation counts exceed the number of answers.

This overlap means coverage describes presence across answers, not market dominance. An answer with no tracked recommendation may still have named companies outside this comparison, so the shares describe the reviewed answers only.

Reach and affirmative recommendation

Ethos ranks 1 by recommendation count. Mentions: 261 (82.08%); recommendations: 207 (65.09%). Top 3 placements: 165 (51.89%); first-place placements: 87 (27.36%).

Wording about the company: 222 positive, 39 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 79.3%. The net framing score was 0.85 (defined in Methodology).

54 mentions had no recorded recommendation. Of recorded recommendations, 79.71% were Top 3 and 42.03% were first-place.

Ethos illustrates why mention and recommendation must be read apart. It appeared in most answers and was recommended in a large majority of them, but a portion of mentions carried no recorded recommendation. Its placements are subsets of those recommendations, not extra wins.

Ladder shows a different pattern: a higher share of its mentions also carried a recommendation, even though its total mentions were lower than Ethos. A tie in recommendation counts would be a tie, not a unique winner.

Recommendation order and placement

Placement describes where a recommended company sat within an answer's ordering. Top-three placements are a subset of recommendations, and first-place placements are a subset of top-three placements, so these figures should not be summed or read as separate victories.

Companies differ in how their recommendations distributed across positions. Some concentrated near the top; others were recommended but rarely placed first. Placement reflects answer ordering, not customer conversion or sales.

Classified framing in context

Framing describes the wording used about a company in the selected answers. Positive, neutral and negative labels classify that wording; they do not measure customer sentiment, reputation or company quality. Neutral wording is not a negative signal, and positive wording does not establish why a recommendation occurred.

Most tracked companies drew no negative wording in this sample, and neutral wording varied. The recommendation-to-mention ratio describes recorded answers, not customers or conversion.

Company results in detail

Ethos

Questions This Section Answers

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

Ethos ranks 1 by recommendation count. Mentions: 261 (82.08%); recommendations: 207 (65.09%). Top 3 placements: 165 (51.89%); first-place placements: 87 (27.36%).

Wording about the company: 222 positive, 39 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 79.3%. The net framing score was 0.85 (defined in Methodology).

54 mentions had no recorded recommendation. Of recorded recommendations, 79.71% were Top 3 and 42.03% were first-place.

From October 2026 to November 2026, Ethos' mention count fell from 319 to 261, while its recommendation count rose from 195 to 207. The recommendation rate was 51.86% and 65.09% respectively.

Ethos led the November recommendation count and appeared in most answers. Its recommendation-to-mention ratio was high, and its placements concentrated toward the top of answer orderings. Framing was overwhelmingly positive with no negative wording recorded.

Compared with October, mentions fell while recommendations rose, and the recommendation rate increased. These are recorded comparisons across separate monthly samples; they do not establish why the counts moved or that any intervention succeeded.

Ladder

Questions This Section Answers

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

Ladder ranks 2 by recommendation count. Mentions: 212 (66.67%); recommendations: 193 (60.69%). Top 3 placements: 149 (46.86%); first-place placements: 53 (16.67%).

Wording about the company: 200 positive, 12 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 91.0%. The net framing score was 0.94 (defined in Methodology).

19 mentions had no recorded recommendation. Of recorded recommendations, 77.20% were Top 3 and 27.46% were first-place.

From October 2026 to November 2026, Ladder's mention count fell from 213 to 212, while its recommendation count rose from 189 to 193. The recommendation rate was 50.27% and 60.69% respectively.

Ladder ranked second by recommendation count and showed the highest recommendation-to-mention ratio among the larger profiles, meaning most of its mentions also carried an endorsement. Its framing was almost entirely positive, with little neutral wording.

Its first-place share was lower than Ethos's despite a strong recommendation base. From October to November, mentions were nearly flat while recommendations rose and the recommendation rate increased; the samples differ, so no cause is inferred.

Policygenius

Questions This Section Answers

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

Policygenius ranks 3 by recommendation count. Mentions: 215 (67.61%); recommendations: 154 (48.43%). Top 3 placements: 123 (38.68%); first-place placements: 33 (10.38%).

Wording about the company: 165 positive, 50 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 71.6%. The net framing score was 0.77 (defined in Methodology).

61 mentions had no recorded recommendation. Of recorded recommendations, 79.87% were Top 3 and 21.43% were first-place.

From October 2026 to November 2026, Policygenius' mention count fell from 235 to 215, while its recommendation count rose from 107 to 154. The recommendation rate was 28.46% and 48.43% respectively.

Policygenius ranked third by recommendation count, with a recommendation-to-mention ratio below the two leaders. A larger share of its mentions carried neutral wording, and its first-place placements were comparatively limited within its recommendations.

Between October and November, mentions fell while recommendations rose substantially, and the recommendation rate increased. Because the monthly answer samples are separate, the comparison shows recorded change only, not improvement or causation.

Bestow

Questions This Section Answers

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

Bestow ranks 4 by recommendation count. Mentions: 49 (15.41%); recommendations: 32 (10.06%). Top 3 placements: 28 (8.81%); first-place placements: 2 (0.63%).

Wording about the company: 38 positive, 11 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 65.3%. The net framing score was 0.78 (defined in Methodology).

17 mentions had no recorded recommendation. Of recorded recommendations, 87.50% were Top 3 and 6.25% were first-place.

From October 2026 to November 2026, Bestow's mention count fell from 57 to 49, while its recommendation count fell from 42 to 32. The recommendation rate was 11.17% and 10.06% respectively.

Bestow ranked fourth, with mentions and recommendations well below the leading three. Its recommendation-to-mention ratio was moderate, and its placements were mostly top-three rather than first-place, so first-place appearances were rare.

From October to November, both mentions and recommendations fell, while the recommendation rate was roughly similar. These are recorded comparisons across separate samples; they do not establish why the counts declined.

Quotacy

Questions This Section Answers

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

Quotacy ranks 5 by recommendation count. Mentions: 14 (4.40%); recommendations: 11 (3.46%). Top 3 placements: 7 (2.20%); first-place placements: 0 (0.00%).

Wording about the company: 13 positive, 1 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 78.6%. The net framing score was 0.93 (defined in Methodology).

3 mentions had no recorded recommendation. Of recorded recommendations, 63.64% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, Quotacy's mention count rose from 9 to 14, while its recommendation count rose from 8 to 11. The recommendation rate was 2.13% and 3.46% respectively.

Quotacy ranked fifth on a small base of mentions and recommendations. Its recommendation-to-mention ratio was fairly high, but with so few answers the ratio is sensitive to individual cases and should be read with that qualification. It recorded no first-place placements.

Mentions and recommendations both rose from October to November, and the recommendation rate increased slightly. The small totals mean month-to-month movement is best treated as a recorded comparison rather than a stable trend.

Everyday Life Insurance

Questions This Section Answers

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

Everyday Life Insurance ranks 6 by recommendation count. Mentions: 3 (0.94%); recommendations: 0 (0.00%). Top 3 placements: 0 (0.00%); first-place placements: 0 (0.00%).

Wording about the company: 0 positive, 3 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 0.0%. The net framing score was 0.00 (defined in Methodology).

3 mentions had no recorded recommendation. Of recorded recommendations, Unavailable were Top 3 and Unavailable were first-place.

From October 2026 to November 2026, Everyday Life Insurance's mention count fell from 5 to 3, while its recommendation count stayed at 0. The recommendation rate was 0.00% and 0.00% respectively.

Everyday Life Insurance recorded a small number of mentions and no recommendations, so its placement counts are also zero. Its mentions carried neutral wording only, and the recommendation-to-mention ratio is undefined because there were no recommendations to divide.

A zero here is a measured result, not a missing observation. Mentions fell from October to November while recommendations stayed at zero; the separate samples do not explain why.

Earlier ranking snapshot context

Questions This Section Answers

• How do the available Life Insurance Companies 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.

The monthly table shows separate selected samples, each with its own answer total, so counts and rates are not directly interchangeable across months. Rank order was stable across the displayed months, but that does not establish rank stability in general or equivalent sampling.

Smaller answer totals in later months do not by themselves explain any company's counts or rates. The comparisons show recorded change only.

What the November Rankings Show

The November results answer several distinct questions. Reach asks whether a company appeared at all; recommendation asks whether an answer affirmatively endorsed it; placement asks where that endorsement sat in the ordering; framing asks how the company was described. A company can be strong on one and weaker on another.

Because placements nest inside recommendations, and recommendations nest inside mentions, the measures should not be combined into a single score. Framing is wording, not sentiment or quality. The figures describe the reviewed AI answers, not customers, sales or verified product facts.

Methodology

Questions This Section Answers

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

This benchmark has partial coverage: 3 of 3 planned question categories contributed usable observations; 0 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; 6 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:

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

Coverage is partial: the findings apply to the available answer set, and the exact collection dates for the original answers were not verified. Each company is counted at most once per qualifying answer, and one answer can mention or recommend several companies, so company totals overlap.

Recommendation requires both affirmative endorsement and positive wording. Top-three and first-place results are included within recommendations, not added to them. The recommendation-to-mention ratio and net framing describe answer wording, not customer conversion, satisfaction or company quality. Monthly samples differ, so comparisons show recorded change without establishing why it occurred.