How AI Search Is Recommending Professional Liability Insurance: Monthly Trends

Executive Summary

The Hartford extended its lead in AI-driven recommendations for professional liability insurance in August 2026, with valid recommendation coverage rising from 77.2% in July to 82.8% in August, a gain of 5.6 points. The gap to the next brand, Next Insurance, widened to 9.8 points as Next Insurance moved from 70.5% to 73.0% coverage. Next Insurance's top-three rate also rose, from 48.5% to 55.4%, though the brand's primary coverage metric remained within normal month-to-month range.

The sharpest decliner was Progressive Commercial, whose coverage fell from 47.2% to 40.8%, a drop of 6.4 points. CNA also declined, dropping from 4.5% to 0.0% coverage; the company was not tracked as a distinct entity in the current month. Its surety-focused counterpart, CNA Surety, appeared for the first time with 3.2% coverage, drawn from 16 valid recommendations. The Hartford and CNA Surety were the two brands whose coverage moved by more than normal month-to-month variation on the rise side; Progressive Commercial and CNA were the two decliners.

The rest of the category held largely steady. Hiscox, Chubb, Thimble, Travelers, and biBERK moved within their normal range, while the gap between The Hartford and Progressive Commercial widened to 42.0 points from 30.0 points, and the gap between biBERK and Progressive Commercial narrowed to 1.8 points from 12.2 points. Four of the ten currently tracked brands moved outside normal range this month, making August a mixed period of a clearer leader pulling ahead alongside a few brands losing ground.

Each monthly run begins with 800 prompt-surface observations (450 unique questions in July, 507 in August) across the benchmark's defined AI/search surface universe. Of those, 800 mentioned a tracked brand or competitor; 519 were relevant and 281 were irrelevant in July, while 525 were relevant and 275 were irrelevant in August. The public metrics use the 491 qualified observations in July and 493 in August that survive both qualification stages.

Key Findings

Benchmark Context

The report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set.

The qualified observation count rose slightly from 491 to 493 between the two months, and the underlying benchmark-level metrics moved as well.

Benchmark-Level Metrics

The recommendation-shaped answer share rose from 44.2% to 56.4% between the two months, meaning AI systems produced recommendation-style responses more often in August within the same category. The data does not establish why the recommendation-shaped share moved; it describes the output distribution the benchmark observed.

AI Recommendation Trend

Leaders Hold While Two Brands Move Outside Normal Range

The Hartford and CNA Surety recorded gains that moved beyond normal month-to-month range on valid recommendation coverage, while Progressive Commercial and CNA recorded declines beyond normal range. The remaining seven brands moved within the range typical for a single month.

What Changed This Month

The Hartford

The Hartford's qualified recommendation coverage rose from 77.2% in July to 82.8% in August, a gain of 5.6 points that moved beyond the brand's normal month-to-month range.

Raw mention presence held mostly steady, moving from 93.7% to 94.9%, meaning the brand was already present in nearly every AI answer. Its top-three rate moved from 60.3% to 64.1%, and its rank-one rate from 38.1% to 40.2%. The Hartford had 198 rank-one recommendations in August out of 408 valid recommendations.

The Hartford has been the category leader by coverage since July, and this month the lead widened further. Its coverage gain occurred in the same month that recommendation-shaped answers rose across the benchmark; the data does not establish a causal link between the two trends.

Highest-priority diagnostic: Which prompt topics in August drove the new rank-one recommendations, and which competitors previously held those positions?

Progressive Commercial

Progressive Commercial's coverage fell from 47.2% in July to 40.8% in August, a drop of 6.4 points that moved beyond the brand's normal month-to-month range — the sharpest decline among the larger brands.

Raw mention presence also fell, from 60.5% to 54.0%. The top-three rate declined from 16.9% to 14.2%, and the rank-one rate from 3.5% to 2.6%. Progressive Commercial earned 201 valid recommendations in August, with 13 rank-one placements.

The gap between Progressive Commercial and The Hartford widened to 42.0 points from 30.0 points, while the gap to biBERK narrowed to 1.8 points from 12.2 points. The benchmark records this shift in relative position without identifying its cause.

Highest-priority diagnostic: Which competitor captured the recommendations Progressive Commercial lost, and in which prompt categories did the presence decline concentrate?

CNA and CNA Surety

CNA's coverage fell from 4.5% in July to 0.0% in August, a decline that moved beyond the brand's normal month-to-month range. In the same month, CNA Surety appeared for the first time at 3.2% coverage, drawn from 16 valid recommendations — also a move beyond normal range.

CNA had 22 valid recommendations in July and no rank-one placements. CNA Surety in August had 24 mentions across 493 observations, a 4.9% raw mention presence rate, and a 0.0% top-three rate.

The pattern is consistent with a naming change in how the benchmark's underlying prompts and answers reference the company, rather than a straightforward loss of visibility, but the data does not establish which explanation applies.

Highest-priority diagnostic: Are AI systems now answering with the Surety-specific brand name for the same prompts that previously returned CNA, or did the underlying prompt set change?

Buyer-Intent Interpretation

In August 2026, all 493 qualified observations fell into the Brand Recommendation cluster. The Pricing & Value and Multi-Brand Comparison clusters were empty, meaning the public benchmark cannot yet answer questions about how AI systems position brands on price or in direct comparison. The recommendation-shaped answer share rose to 56.4%, but the commercial comparison and pricing questions remain unanswered by this dataset.

Brand Opportunity Summary

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations (query, surface, recommendation outcome, rank, sentiment, and citations where exposed). Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically treated as proof of causation.

About This Benchmark

This report is part of the LLM Authority Index AI Market Discovery research program.

• AI Industry Market Discovery
• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

• Small-count movement: CNA Surety's 3.2% coverage is based on 16 valid recommendations out of 493 observations. Its debut should be read as an early signal, not a settled trend.
• Qualified denominator vs. raw collection: All percentage metrics use the 493 qualified observations, not the 800 raw prompt-surface observations. This excludes irrelevant and reserved prompts.
• Month-over-month movement identifies changes worth investigating; it does not by itself establish the cause of those changes.
• Naming pattern: CNA's decline to 0.0% and CNA Surety's debut at 3.2% may reflect a change in how the benchmark's data captures the company's name, not a loss of underlying visibility.

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

Beneath the aggregate percentages sit the questions that matter: which high-intent prompts is a brand winning, which competitor takes the recommendation when it loses, what attributes AI systems associate with each option, and which external sources shape those answers. The benchmark shows the scoreboard; it does not explain the plays that produced it.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It can help explain why The Hartford widened its lead, why Progressive Commercial lost ground, and what it would take for a specific brand to improve its position.

Request an AI visibility audit