How AI Search Is Recommending Mesothelioma Lawyers: Monthly Trends

Executive Summary

Simmons Hanly Conroy remains the clear coverage leader in AI-driven recommendations for mesothelioma lawyers for the third consecutive month, holding 67.0% valid recommendation coverage in September 2026. The gap to the next closest brand, Weitz & Luxenberg at 37.6%, is 29.4 points. While the top of the category held, September was marked by continued compression: four brands registered significant declines from the July baseline, though no brand exceeded normal month-to-month variation between August and September.

The largest story across the full series is a two-month contraction. Weitz & Luxenberg saw the steepest baseline-to-current decline, falling 20.6 points from 58.2% in July to 37.6% in September. Simmons Hanly Conroy dropped 17.9 points from 84.9% to 67.0% over the same period. Shrader & Associates fell 10.0 points from 18.1% to 8.1%, while Goldberg Persky White declined 3.3 points from 4.7% to 1.4%. Between August and September, however, no brand moved beyond its typical range; the category held relatively stable after the larger July-to-August shifts.

Sokolove Law remains the most stable major brand, holding at 18.6% in September versus 22.8% in July, a 4.2-point decline that stayed within normal variation. Cooney & Conway (11.3%), Kazan McClain (6.8%), and Shrader & Associates (8.1%) occupy the middle tier with single-digit to low-double-digit coverage. The lower tier, including Belluck & Fox at 3.6%, Nemeroff Law at 4.1%, and Galiher DeRobertis at 1.8%, remains in stable but limited territory.

Each monthly run begins with 300 prompt-surface observations (238 unique questions) in July, 761 prompt-surface observations (614 unique questions) in August, and 428 prompt-surface observations (362 unique questions) in September across the benchmark's defined AI/search surface universe. Of those, 300 mentioned a tracked brand or competitor in July and 428 did so in September; 236 were relevant and 64 were irrelevant in July, while 252 were relevant and 176 were irrelevant in September. The public metrics use the 232 qualified observations in July and 221 qualified observations in September 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 benchmark set is the denominator used throughout this report for every brand-level percentage that follows.

Benchmark-Level Metrics

August drew from a substantially larger prompt funnel (761 total prompts) than either July (300) or September (428). The recommendation-shaped answer share rose from 52.6% in July to 58.8% in September, while the valid recommendation shortlist share fell from 87.5% to 70.6%, reflecting a shift in how many observations carried usable recommendation formats.

AI Recommendation Trend

Leadership Persists, but the Upper Tier Has Compressed Since July

Simmons Hanly Conroy retains the top position at 67.0% coverage in September, down 17.9 points from July, with Weitz & Luxenberg holding second at 37.6% and Sokolove Law third at 18.6%. The category-level change from July to September came from the combination of several significant declines rather than a single dominant mover, and between August and September no brand exceeded normal month-to-month variation, meaning the compression was concentrated in the July-to-August window and the category has since settled.

What Changed This Month

Simmons Hanly Conroy: Two-Month Decline, Leadership Unchallenged

Simmons Hanly Conroy's valid recommendation coverage fell from 84.9% in July to 67.0% in September, a 17.9-point significant decline. The firm remains the category leader by a wide margin; the gap to Weitz & Luxenberg widened from 26.7 points in July to 29.4 points by September as both brands declined at different rates.

The firm's top-three rate dropped from 79.7% to 61.5%, and its rank-one rate fell from 50.9% to 41.6%. Presence also slipped, with raw mention presence declining from 89.7% to 81.0%. In absolute terms, the firm was recommended in 148 of 221 qualified observations in September versus 197 of 232 in July.

The distinction to notice: Simmons Hanly Conroy is still recommended in two-thirds of qualified observations, and its rank-one rate of 41.6% remains well above every other tracked brand. The frequency of first-position recommendations has eroded, but the concentration of that advantage is still substantial.

Highest-priority diagnostic: Which prompt types no longer return Simmons Hanly Conroy as the top recommendation, and which brands are taking those placements?

Weitz & Luxenberg: Largest Baseline-to-Current Decline

Weitz & Luxenberg experienced the steepest coverage drop of any brand across the full series, falling from 58.2% in July to 37.6% in September, a 20.6-point significant decline. Most of that movement occurred between July and August (19.8 points), with only a 0.8-point change from August to September.

The firm's top-three rate fell from 53.9% to 34.4%, and its rank-one rate dropped from 16.4% to 11.3%. Raw mention presence declined from 62.1% to 48.4%. In absolute terms, Weitz & Luxenberg received 83 valid recommendations in September versus 135 in July.

The distinction to notice: Weitz & Luxenberg remains solidly in second place, but the gap to Sokolove Law in third has narrowed to 19.0 points from 35.4 points in July. The firm's presence in fewer than half of qualified observations marks a shift from its July position of appearing in over 60% of them.

Highest-priority diagnostic: Which competitor absorbed Weitz & Luxenberg's lost recommendation share, and was the decline concentrated in specific AI surfaces or prompt types?

Shrader & Associates: Significant Decline From the Mid-Tier

Shrader & Associates dropped from 18.1% in July to 8.1% in September, a 10.0-point significant decline. The firm's top-three rate fell from 10.3% to 3.6%, and rank-one recommendations fell from 1.7% to zero.

The firm recorded 18 valid recommendations in September versus 42 in July. Raw mention presence declined from 19.0% to 11.3%, and net sentiment slipped from 1.0 to 0.7, the second consecutive month with that lower sentiment reading. Between August and September, however, coverage was stable at 8.1% versus 7.6%, a 0.5-point move within normal range.

The distinction to notice: Shrader & Associates' coverage has stabilized after the sharp July-to-August drop, but remains well below its July level of 18.1%. The firm has no rank-one recommendations in September, down from a 1.7% rank-one rate in July, suggesting its placements, when they occur, are not at the top of the list.

Highest-priority diagnostic: Did Shrader & Associates lose coverage across all surfaces in the July-to-August window, and which competitor captured the first-position recommendations it lost?

Goldberg Persky White: Significant Decline on Small Volume

Goldberg Persky White fell from 4.7% in July to 1.4% in September, a 3.3-point significant decline. The firm recorded only 3 valid recommendations in September versus 11 in July, a small count that requires caution in interpretation.

Top-three rate dropped from 3.9% to 0.9%, and rank-one rate fell from 0.9% to zero. Raw mention presence declined from 4.7% to 1.4%. Net sentiment held at 1.0, indicating that when Goldberg Persky White does appear, the context remains universally positive.

The distinction to notice: with only 3 valid recommendations in September, a single prompt carries substantial weight. The firm's presence is now marginal, but its sentiment is perfect, meaning the issue is frequency of appearance rather than the context of those appearances.

Highest-priority diagnostic: Which surfaces or prompts continue to include Goldberg Persky White at all, and what changed in the July-to-August window?

Buyer-Intent Interpretation

The September 2026 qualified observations fell entirely into the brand recommendation cluster. AI systems are answering "who should I hire" questions with named firms, but the benchmark captured no qualified observations in the pricing and value or multi-brand comparison clusters. The public benchmark cannot yet speak to how AI systems discuss cost structures, fee arrangements, or head-to-head firm comparisons. Those commercial questions remain largely unexamined by the current prompt set, and firms should treat the absence of data in these clusters as a gap in visibility intelligence rather than evidence of no activity.

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

Report-Specific Interpretation Notes

• Movement analysis compares the qualified benchmark set between July and September 2026, with August referenced for intermediate context; the series spans three comparable months.
• Small observation counts apply to several brands; Galiher DeRobertis (4 recommendations) and Goldberg Persky White (3 recommendations) should be read with caution because single prompts carry more weight at that scale. Kazan McClain (15), Nemeroff Law (9), and Belluck & Fox (8) also sit on small bases.
• Movement analysis identifies changes worth investigating; month-over-month movement does not by itself establish the cause of those changes. The absence of significant movement between August and September does not mean the earlier shifts have been explained.

Next Step

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

The aggregate percentages raise questions the public benchmark cannot answer. Which high-intent prompts is each brand winning? When a brand loses the recommendation, which competitor takes its place? What attributes do AI systems associate with each firm? Which external sources are shaping those answers? Answering these questions requires examining the underlying prompt, surface, and evidence patterns behind the movement.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. Where the public benchmark shows the score, a company-level audit shows the drivers.

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