The headline numbers

If a buyer asked the five major AI engines for a commercial insurance broker this quarter, three names dominated the answers. Meridian Risk Partners held the top slot for the ninth consecutive month, appearing in 41 percent of all recorded recommendations. But the story of Q2 is churn: of the ten brokers most recommended in March, only seven were still being recommended in May.

41% of recorded answers named Meridian Risk Partners · 2 brokers disappeared from ChatGPT's answers entirely · Crestline Cover entered the top five from nowhere, on the strength of 11 new citations Source: Fortitude Vault, 4,820 recorded answers, 1 Mar to 31 May 2026. Illustrative sample data.

That churn rate matters more than the league table. AI engines are not search rankings; they re-evaluate their sources continuously, and a brand that stops earning citations can fall out of the answer in weeks, not years. Two of the brokers who vanished this quarter had strong Google rankings throughout. Rankings did not save them.

The index: top ten by share of recommendations

Share of recommendations is the percentage of recorded answers in which each brand was named, across all four engines, weighted equally. Movement is against the Q1 index.

#BrandSharevs Q1Engines naming
1Meridian Risk Partners41%+35/5
2Halcyon Brokers33%-45/5
3Crestline Cover24%+24 (new)4/5
4Bram & Wexley19%-24/5
5Saxon Marsh Insurance14%+13/5
6Northgate Risk11%-63/5
7Pelham Cover Group9%+23/5
8Ashdown Broking7%+7 (new)2/5
9Ferris & Hale6%-12/5
10Wrenfield Insurance5%-32/5
Figure 1: Share of AI recommendations, UK commercial insurance broking, Q2 2026. Fortitude Vault. Illustrative sample data.

The quarter's movers

Crestline Cover is the quarter's story. In March the Vault had never recorded an engine naming them. By the last week of May they appeared in nearly a quarter of all answers, and in 38 percent of ChatGPT's. The climb maps cleanly onto their citation record: a commissioned data study on underinsurance in UK manufacturing was picked up by two trade publications in early April, and the engines began citing those articles within three weeks.

Northgate Risk moved the other way. Their share fell six points after their highest-cited source, a 2023 industry roundup, dropped out of the engines' answers. Nothing replaced it. Their website content has not changed since January; the engines simply found fresher sources for the same questions, and those sources talk about other brokers.

What moved the answers

Three patterns from this quarter's data, consistent with what the Vault sees across categories:

Fresh third-party citations beat old authority. Every riser this quarter earned new coverage in sources the engines already trusted. No riser got there on their own website alone.

Engines disagree, and the gaps are exploitable. Crestline cracked ChatGPT and Perplexity months before Gemini noticed them. A brand watching engine-level data can see which doors are open.

Absence is silent. The two brokers who vanished from ChatGPT's answers saw no alarm, no notification, no traffic graph falling off a cliff. The deals simply started forming elsewhere. This is why we keep saying: if you do not measure the answers, you will not know.

Methodology. The Fortitude Vault records answers from ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews to a canonical library of buyer-intent questions, maintained per category by Fortitude Media. This index covers 67 questions about UK commercial insurance broking, asked weekly from 1 March to 31 May 2026, producing 4,820 recorded answers. Mentions are detected at entity level with negative-context filtering. Share of recommendations is the percentage of answers naming each brand, engines weighted equally. The Vault records our own runs on our own question library; no customer prompts or account data are used. This report was drafted automatically from Vault data and edited by a human before publication.

The next UK Insurance Broking index publishes in September. Monthly movers reports publish in the first week of each month.