Aon Edge Appears in 19.4% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Answer Capsule

In November 2026, Aon Edge appeared in 31 of 160 AI answers included in the Flood Insurance benchmark (19.38%). It received 29 recommendations (18.13%), with 15 Top 3 placements and 2 first-place recommendations. A mention means the company appeared in an answer; a recommendation means the answer affirmatively endorsed it.

Our plan compares the company with its competitors, checks conflicting AI claims against reliable sources, and identifies website pages, third-party sources and buyer questions to address. The historical results show how the figures changed across available months. Different monthly samples limit those comparisons, and conflicting AI claims require verification before corrections are proposed.

Current AI visibility

Questions This Section Answers

• How do Aon Edge mentions, recommendations and placements compare with its Flood Insurance peers?

Aon Edge recorded 31 mentions (19.38%) and 29 recommendations (18.13%) across 160 answers included in the benchmark. Top 3 placements numbered 15; first-place recommendations numbered 2. Framing among its mentions was 29 positive, 2 neutral and 0 negative.

Aon Edge is recommended in most answers where it appears, which is a stronger position than its overall share suggests. The gap sits in placement: it is named often but rarely leads the answer, so buyers see the brand without seeing it chosen first.

That pattern matters because recommendation and position do different work. Being endorsed builds consideration; being placed first shapes the shortlist a buyer acts on. The agency would treat reach and placement as separate goals rather than one visibility score.

A proposed scorecard would track mentions, recommendations and placement side by side, so progress in one is not mistaken for progress in another.

What changed since last month

Questions This Section Answers

• How did Aon Edge counts and coverage differ across the available monthly snapshots?

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

From October 2026 to November 2026, Aon Edge's mention count rose from 21 to 31, while its recommendation count rose from 15 to 29. The recommendation rate was 5.79% and 18.13% respectively.

The November sample shows more mentions and more recommendations than October, and a higher share of answers on both measures. Placement counts also rose. These are observed movements in separate monthly samples, not a trend line.

The samples differ between months, so the comparison shows what was recorded, not why it changed. A larger share in one month does not establish that anything improved in the market or in the company's standing.

The agency would keep reporting each month on its own terms and avoid reading a single month as evidence of momentum.

Step 1. Measure

Questions This Section Answers

• What should the agency measure and verify first for Aon Edge?

AI answers contained 3 conflicting claims about Aon Edge: 0 critical, 0 high, 2 medium, 1 low. Of these, 0 were rated critical or high priority; the critical claims are included in that total. These ratings help prioritize fact-checking. They do not establish that a company or publisher made an error.

The benchmark recorded a small set of conflicting claims about Aon Edge, mostly at medium severity. None were rated critical or high, so fact-checking can proceed in a measured order rather than as an emergency.

A visibility comparison alongside that claim list would let the client see where reach is strong and where wording is contested, and set priorities from both. Severity ratings order the work; they do not establish that the company or a publisher made an error.

The agency would build a scoped fact-review register, assigning each claim an owner, an evidence requirement and a review status before any correction is considered.

Step 2. Make the website consistent

Questions This Section Answers

• Which recorded claim differences about Aon Edge should be verified before proposed page edits?

Both columns quote AI answers, not verified company facts. Resolve the entity, date and source before deciding whether a correction is warranted; different dates can explain an apparent conflict.

The disputed topics concern discount language against NFIP and the maximum coverage limits, including building coverage. Both columns in the review table quote AI answers, not verified company facts, so neither side can be treated as correct yet.

The agency would verify each topic against current primary sources, confirm the entity and date involved, and only then decide whether a page brief or a correction is warranted. Different dates can explain an apparent conflict.

Where facts are confirmed, briefs would state approved figures plainly so answers have a consistent basis to draw on.

Step 3. Align the external narrative

Questions This Section Answers

• Which cited third-party pages are relevant to fact review for Aon Edge?

These pages were selected because they relate to the company in the captured answers. Their current contents still need checking before any correction request. A page linked to a conflicting claim is not necessarily its cause, and the same answer may contribute to more than one row.

Several cited pages appear repeatedly alongside answers that mention Aon Edge, including comparison articles and insurer and government pages. Citation does not show that a page influenced an answer, and a page linked to a conflicting claim is not necessarily its cause.

The agency would review the selected pages for current content, then prepare evidence-backed requests only where a specific, verifiable issue is found. Publisher control and publisher error are not assumed.

Requests would be logged separately from confirmed edits and from no-change decisions, so the client can see what was asked and what came back.

Step 4. Optimize priority company pages

Questions This Section Answers

• Which observed Aon Edge website pages should receive review briefs?

The company's website was cited 3 times across 2 distinct page addresses; the table shows 2 pages selected for review. Zeros in the answer columns mean no matching answers were recorded. A cited page is not automatically a page that accompanied a recommendation.

Only a small number of company pages were cited in the captured answers, including the homepage and a resource comparing private flood insurance with NFIP. That is a narrow base for answers to draw on.

The agency would prepare page briefs using approved facts and the buyer questions observed in the research, checking existing coverage before proposing anything new. A cited page is not automatically a page that accompanied a recommendation.

Briefs would be reviewed internally before publication, with claims traced to primary sources.

Step 5. Publish around buyer questions

Questions This Section Answers

• Which observed buyer questions support content briefs for Aon Edge?

These are recorded answer observations, not search volume, verified demand, or proof of missing website content.

The recorded questions cluster around which company is best for flood insurance, with a Florida variant and a shorter phrasing also appearing. Aon Edge is mentioned and recommended in several of these answers, so the brand is already in the conversation.

These are answer observations, not search volume or proof that the website lacks content. The agency would check existing pages first, then draft buyer-question briefs that answer the comparison directly with approved facts.

Each brief would name the question it serves and the evidence behind every claim.

Our 90-day action plan

Questions This Section Answers

• How should the agency sequence the proposed Aon Edge work and judge completion?

The first month establishes the baseline scorecard, a scoped fact-review register and a shortlist of pages and sources, each with an owner and review status. Nothing is corrected at this stage.

The second month produces approved page briefs and justified publisher requests, with confirmed edits, no-change decisions, requests and responses recorded separately. The third month adds buyer-content briefs and a fresh scorecard.

Delivered work is reported apart from measured answer outcomes, and no gain is promised from completing it.

Methodology

Questions This Section Answers

• How are Aon Edge answer metrics and citation populations defined?

This report covers 2026-11. The exact dates when the original AI answers were collected have not been verified. The visibility rates use 160 answers that met the benchmark's inclusion rules. A company is recommended only when the answer both endorses it and uses positive wording. Top 3 and first-place counts are part of those recommendations, not extra recommendations.

An answer can mention or recommend several companies, so company counts cannot be added to find the number of distinct answers. The net sentiment score is positive minus negative mentions, divided by all company mentions; it describes answer wording, not customer satisfaction.

The wider citation analysis covers 800 captured answers and 4985 appearances of cited URLs. Citation appearances across all captured answers differ from the number of benchmark answers citing a page and the number that also recommend a company. The current contents of cited pages and disputed company claims still need independent verification.

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.

The visibility rates rest on answers that met the benchmark's inclusion rules, and the exact collection dates for the original answers have not been verified. A company counts as recommended only when an answer endorses it with positive wording; placement counts sit inside recommendations rather than adding to them.

Answers can mention several companies, so company counts do not sum to distinct answers. Monthly samples differ, and comparisons show what was recorded, not why. Cited pages and disputed claims still need independent verification.

Our first three priorities

First, verify the disputed coverage-limit and discount claims against current primary sources, since those topics carry the most weight in the review list and shape what buyers are told about limits.

Second, prepare page briefs for the small set of company pages answers already cite, using approved facts and the buyer questions recorded in the research. Third, review the most-cited external comparison pages and issue evidence-backed requests only where a specific issue is confirmed.

Each step has a named owner and a review status, and completed work will be reported separately from any change in answer visibility.