Professional & Management Liability Insurance AI Visibility Ranking Trends - November 2026

Answer capsule

The November 2026 Professional & Management Liability Insurance benchmark compares 10 companies across 225 AI answers that met its inclusion rules. Gallagher leads with 45 recommendations (20.00% of answers). At least one tracked company was recommended in 53 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 Professional & Management Liability Insurance

Industry leaderboard

Questions This Section Answers

• How do Professional & Management Liability Insurance rank by recorded AI recommendations in November 2026?

The leaderboard orders companies by recommendation count, so it reflects how often each firm received an affirmative endorsement in the reviewed AI answers, not how often it appeared. Gallagher, Aon and Marsh form a close top group, and their order depends on small count differences rather than a wide gap.

Mentions, recommendations and placements answer different questions. A company can be named frequently yet recommended rarely, and placement counts are nested within recommendations rather than added to them. Ties reflect equal recommendation counts, so shared ranks should not be read as a unique winner.

Key findings

Tracked-company answer coverage

Questions This Section Answers

• How often did the November 2026 Professional & Management Liability Insurance answer sample recommend any tracked company?

53 distinct answers recommended at least one tracked company. Counting each company recommendation separately gives 159, 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 only a minority recommended one. That gap shows that appearing in an answer and being affirmatively endorsed are distinct outcomes, and coverage of the tracked set does not imply market dominance.

Because one answer can recommend several companies, company-level totals exceed the number of answers with any recommendation. Answers without a tracked recommendation may still have named firms outside this comparison, so the coverage figures describe the tracked set only.

Reach and affirmative recommendation

Gallagher ranks 1 by recommendation count. Mentions: 175 (77.78%); recommendations: 45 (20.00%). Top 3 placements: 25 (11.11%); first-place placements: 3 (1.33%).

Wording about the company: 62 positive, 111 neutral, 2 negative mentions. The proportion of mentions that also included a recommendation was 25.7%. The net framing score was 0.34 (defined in Methodology).

130 mentions had no recorded recommendation. Of recorded recommendations, 55.56% were Top 3 and 6.67% were first-place.

Gallagher's profile shows why reach and endorsement must be read separately: the company was mentioned in most answers but recommended in a smaller share, and many mentions carried no recorded recommendation. Mention presence therefore describes visibility in the answers, not affirmative support.

Placement figures are subsets of recommendations, so first-place counts sit inside Top 3 counts, which sit inside recommendations. The recommendation-to-mention ratio describes the recorded answers only and does not measure customer behavior or conversion.

Recommendation order and placement

Placement describes where a recommended company appeared in an answer's ordering, and the counts are nested: first-place results are part of Top 3 results, which are part of recommendations. They should not be summed or treated as separate wins.

Recommendation-to-mention ratios vary across companies with similar mention totals, which shows that being named and being endorsed are different measurements. A high ratio on a very small base, such as Embroker's, needs that sparse base kept in view.

Classified framing in context

Framing describes the wording used around a company in the selected answers. Most mentions across the larger firms were neutral, with positive wording less common and negative wording rare or absent. Neutral wording is not a negative signal, and positive wording does not establish why a recommendation occurred.

Framing is not customer sentiment or a measure of company quality. The classified wording reflects how these particular answers described each firm, and the counts should be read alongside mention and recommendation totals rather than as a reputation score.

Company results in detail

Gallagher

Questions This Section Answers

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

Gallagher ranks 1 by recommendation count. Mentions: 175 (77.78%); recommendations: 45 (20.00%). Top 3 placements: 25 (11.11%); first-place placements: 3 (1.33%).

Wording about the company: 62 positive, 111 neutral, 2 negative mentions. The proportion of mentions that also included a recommendation was 25.7%. The net framing score was 0.34 (defined in Methodology).

130 mentions had no recorded recommendation. Of recorded recommendations, 55.56% were Top 3 and 6.67% were first-place.

From October 2026 to November 2026, Gallagher's mention count rose from 36 to 175, while its recommendation count rose from 15 to 45. The recommendation rate was 11.72% and 20.00% respectively.

Gallagher leads the recommendation ranking, with a large mention base and a substantial share of mentions that also carried an endorsement. Most of its wording was neutral, with positive wording present and negative wording rare. Its placements are nested within recommendations, and first-place results are a small subset of Top 3 results.

The month-to-month comparison shows both mentions and recommendations higher than in the prior sample, while the recommendation rate also rose. Because the monthly samples differ, the recorded change does not establish why it occurred.

Aon

Questions This Section Answers

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

Aon ranks 2 by recommendation count. Mentions: 207 (92.00%); recommendations: 43 (19.11%). Top 3 placements: 23 (10.22%); first-place placements: 2 (0.89%).

Wording about the company: 58 positive, 149 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 20.8%. The net framing score was 0.28 (defined in Methodology).

164 mentions had no recorded recommendation. Of recorded recommendations, 53.49% were Top 3 and 4.65% were first-place.

From October 2026 to November 2026, Aon's mention count rose from 56 to 207, while its recommendation count rose from 30 to 43. The recommendation rate was 23.44% and 19.11% respectively.

Aon ranks second by recommendation count on a very large mention base, giving it high visibility alongside a moderate recommendation-to-mention ratio. Its wording was predominantly neutral, with positive mentions recorded and no negative ones. Top 3 placements form roughly half of its recommendations, while first-place results are a small subset.

Compared with the prior sample, mentions and recommendations both rose while the recommendation rate was slightly lower. The separate monthly samples do not explain that pattern.

Marsh

Questions This Section Answers

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

Marsh ranks 3 by recommendation count. Mentions: 216 (96.00%); recommendations: 42 (18.67%). Top 3 placements: 25 (11.11%); first-place placements: 23 (10.22%).

Wording about the company: 59 positive, 157 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 19.4%. The net framing score was 0.27 (defined in Methodology).

174 mentions had no recorded recommendation. Of recorded recommendations, 59.52% were Top 3 and 54.76% were first-place.

From October 2026 to November 2026, Marsh's mention count rose from 58 to 216, while its recommendation count rose from 24 to 42. The recommendation rate was 18.75% and 18.67% respectively.

Marsh ranks third by recommendation count but stands out for placement: a large share of its recommendations were first-place results, and first-place counts are nested within its Top 3 totals. Its mention base was the largest among tracked firms, with mostly neutral wording and no negative mentions.

Mentions and recommendations were both higher than in the prior sample, while the recommendation rate was nearly level. The differing monthly samples limit any inference about why.

Brown & Brown

Questions This Section Answers

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

Brown & Brown ranks 4 by recommendation count. Mentions: 79 (35.11%); recommendations: 17 (7.56%). Top 3 placements: 1 (0.44%); first-place placements: 0 (0.00%).

Wording about the company: 22 positive, 57 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 21.5%. The net framing score was 0.28 (defined in Methodology).

62 mentions had no recorded recommendation. Of recorded recommendations, 5.88% were Top 3 and 0.00% were first-place.

From October 2026 to November 2026, Brown & Brown's mention count rose from 3 to 79, while its recommendation count rose from 1 to 17. The recommendation rate was 0.78% and 7.56% respectively.

Brown & Brown holds a mid-table recommendation count on a moderate mention base, with a recommendation-to-mention ratio comparable to the larger firms. Its placements are sparse: a single Top 3 result and no first-place results, so placement is a small part of its recommendation profile. Wording was mostly neutral with some positive mentions.

Both mentions and recommendations were higher than in the prior sample, and the recommendation rate rose. The samples differ, so the change is recorded rather than explained.

Lockton

Questions This Section Answers

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

Lockton ranks 5 by recommendation count. Mentions: 76 (33.78%); recommendations: 11 (4.89%). Top 3 placements: 2 (0.89%); first-place placements: 1 (0.44%).

Wording about the company: 19 positive, 57 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 14.5%. The net framing score was 0.25 (defined in Methodology).

65 mentions had no recorded recommendation. Of recorded recommendations, 18.18% were Top 3 and 9.09% were first-place.

From October 2026 to November 2026, Lockton's mention count rose from 29 to 76, while its recommendation count fell from 13 to 11. The recommendation rate was 10.16% and 4.89% respectively.

Lockton's recommendation count places it in the middle of the ranking, but its recommendation-to-mention ratio is lower than most peers, meaning many mentions carried no endorsement. Its placements are few, with a small number of Top 3 results and one first-place result nested within them. Wording was largely neutral with some positive mentions.

Mentions rose from the prior sample while recommendations fell, and the recommendation rate was lower. The separate samples do not establish a cause for that divergence.

Embroker

Questions This Section Answers

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

Embroker ranks 6 by recommendation count. Mentions: 1 (0.44%); recommendations: 1 (0.44%). Top 3 placements: 1 (0.44%); first-place placements: 1 (0.44%).

Wording about the company: 1 positive, 0 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 100.0%. The net framing score was 1.00 (defined in Methodology).

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

From October 2026 to November 2026, Embroker's mention count fell from 14 to 1, while its recommendation count fell from 8 to 1. The recommendation rate was 6.25% and 0.44% respectively.

Embroker's profile rests on a single mention that also carried a recommendation and a first-place placement, producing a very high recommendation-to-mention ratio and a positive framing score. Those figures are arithmetically valid but rest on a sparse base, so they should not be read as a stable pattern.

Both mentions and recommendations were far lower than in the prior sample. The recorded comparison does not establish why the counts changed.

Axis Insurance Services

Questions This Section Answers

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

Axis Insurance Services ranks 7 by recommendation count. Mentions: 0 (0.00%); recommendations: 0 (0.00%). Top 3 placements: 0 (0.00%); first-place placements: 0 (0.00%).

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

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

From October 2026 to November 2026, Axis Insurance Services' mention count fell from 2 to 0, while its recommendation count stayed at 0. The recommendation rate was 0.00% and 0.00% respectively.

Axis Insurance Services recorded no mentions and no recommendations in this sample, so its placement counts are also zero and ratios requiring a nonzero base are undefined. These are measured zero results, not missing observations.

Mentions were lower than in the prior sample while recommendations remained at zero. The comparison is recorded without inferring a cause, and the zero results describe only the answers reviewed.

Professional Liability Insurance Group

Questions This Section Answers

• What do the November 2026 AI answer results show about Professional Liability Insurance Group mentions, recommendations and placement?

Professional Liability Insurance Group ranks 7 by recommendation count. Mentions: 0 (0.00%); recommendations: 0 (0.00%). Top 3 placements: 0 (0.00%); first-place placements: 0 (0.00%).

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

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

From October 2026 to November 2026, Professional Liability Insurance Group's mention count stayed at 0, while its recommendation count stayed at 0. The recommendation rate was 0.00% and 0.00% respectively.

Professional Liability Insurance Group recorded no mentions and no recommendations in this sample, leaving placement counts at zero and ratios undefined for lack of a base. These are valid measured zeros rather than absent data.

Mentions and recommendations were both at zero in the prior sample as well. The unchanged zero results describe the reviewed answers only and do not establish anything about the company beyond them.

TechInsurance

Questions This Section Answers

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

TechInsurance ranks 7 by recommendation count. Mentions: 3 (1.33%); 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, TechInsurance's mention count rose from 2 to 3, while its recommendation count fell from 1 to 0. The recommendation rate was 0.78% and 0.00% respectively.

TechInsurance was mentioned a few times but received no recommendations, so its recommendation-to-mention ratio is zero and its placement counts are zero. All of its recorded wording was neutral, which is neither an endorsement nor a negative signal.

Mentions were slightly higher than in the prior sample while recommendations fell to zero. The samples differ, so the recorded change does not explain why no endorsement appeared.

The Baldwin Group Innovation Practice (formerly Founder Shield)

Questions This Section Answers

• What do the November 2026 AI answer results show about The Baldwin Group Innovation Practice (formerly Founder Shield) mentions, recommendations and placement?

The Baldwin Group Innovation Practice (formerly Founder Shield) ranks 7 by recommendation count. Mentions: 0 (0.00%); recommendations: 0 (0.00%). Top 3 placements: 0 (0.00%); first-place placements: 0 (0.00%).

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

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

From October 2026 to November 2026, The Baldwin Group Innovation Practice (formerly Founder Shield)'s mention count fell from 13 to 0, while its recommendation count fell from 5 to 0. The recommendation rate was 3.91% and 0.00% respectively.

The Baldwin Group Innovation Practice recorded no mentions and no recommendations in this sample, so placement counts are zero and ratios are undefined. These are measured zero results rather than missing observations.

Both mentions and recommendations were lower than in the prior sample, when the firm had appeared and been recommended. The separate samples do not establish why the counts changed, and the comparison is recorded without causal inference.

Earlier ranking snapshot context

Questions This Section Answers

• How do the available Professional & Management Liability Insurance snapshots from October 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 earlier snapshot is a separate monthly sample with a different answer total and a different set of AI services, so counts and rates are not directly equivalent across months. Rank changes between the two months should be read as recorded positions in different samples.

A changed count or rate does not demonstrate improvement, loss of standing or the effect of any intervention. The comparison shows what was recorded; it does not establish why.

What the November Rankings Show

The November results show that reach, recommendation, placement and framing answer different questions. A company can be named in most answers yet endorsed in far fewer, and placement describes ordering within endorsements rather than additional support. Reading these measures together gives a fuller picture than any single column.

The leaderboard orders firms by recommendation count, but the close top group and the nested placement counts mean small differences should not be overread. Framing adds context about wording without measuring sentiment or quality. The monthly comparison is a separate sample, so changes are recorded rather than explained.

Methodology

Questions This Section Answers

• How were the November 2026 Professional & Management Liability Insurance 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; 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:

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

The benchmark covers a partial set of question categories, and findings apply only to the answers reviewed. The reporting month labels the period, but exact collection dates were not verified. Each company is counted at most once per answer, and recommendation requires both affirmative endorsement and positive wording.

Rates use the full benchmark answer total, and placement results are nested within recommendations. The recommendation-to-mention ratio and net framing describe answer wording, not customers, sales or company quality. Monthly samples differ in size and services, so comparisons show recorded change without establishing cause.