How AI Search Is Recommending Bankruptcy Lawyers: Monthly Trends

Executive Summary

Upsolve remains the clear coverage leader in August 2026, holding valid recommendation coverage of 52.0% against the next-highest firm at 2.7%, a leadership gap of 49.3 points. August was a quiet month for the category: no brand crossed the threshold the benchmark uses to flag a meaningful month-over-month move in valid recommendation coverage, and Upsolve's position at the top of the category stayed stable.

Cibik Law was the only brand to add coverage this month, entering the public benchmark with 1.4% coverage in August after recording no valid recommendations in July (2 of 146 qualified observations, both positive). The largest declines in coverage were John T. Orcutt and Sasser Law Firm, each down 1.6 points from 4.3% to 2.7%; neither move crossed the category's normal range of month-to-month variation. All ten tracked brands are classified as stable on the primary coverage metric this month.

Within that otherwise quiet coverage picture, Upsolve's top-three recommendation rate moved from 19.1% in July to 6.2% in August, and its rank-one rate moved from 17.7% to 6.2%. Those are placement-level figures rather than the benchmark's primary coverage metric, so they are reported here as data points for further inspection rather than as a confirmed category-level shift. Upsolve's own coverage figure (down from 57.5% to 52.0%) and raw presence (up slightly from 89.4% to 89.7%) both stayed within the category's normal month-to-month range.

This benchmark tracks 385 prompt-surface observations (322 unique questions) collected in August 2026, up from 301 observations (252 unique questions) in July 2026. Of the August observations, 385 mentioned a tracked brand or competitor; 264 were relevant and 121 were irrelevant. The public benchmark uses the 146 observations that passed both qualification stages in August, compared with 141 in July.

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 set grew by only 5 observations from July to August even as the raw collection expanded by 84 prompts. The reserved pool of relevant-but-not-yet-qualified prompts also grew, from 64 to 118, which may be drawn into future months.

Benchmark-Level Metrics

AI Recommendation Trend

Upsolve Leads But the Second Tier Is Nearly Flat

The category is defined by a single dominant leader and a long tail of low-coverage firms. Upsolve's 52.0% coverage stands 49.3 points above every other brand, and no brand outside Upsolve exceeded 2.7% in either month.

No brand crossed the threshold for a meaningful coverage move this month. Upsolve's top-three recommendation rate did move from 19.1% in July to 6.2% in August, a placement-level data point outside the primary coverage metric. The remaining category-level change was the combination of several small, non-significant movements among the second-tier brands.

What Changed This Month

Upsolve: Coverage Holds Steady While Placement Rates Move Lower

Upsolve's valid recommendation coverage moved from 57.5% in July to 52.0% in August, a change that stayed within the category's normal month-to-month range for this metric. Its raw presence held essentially flat, up slightly from 89.4% to 89.7%, meaning the brand appeared in roughly the same share of qualified observations in both months.

Placement-level figures moved more than coverage did: top-three rate went from 19.1% to 6.2%, and rank-one rate from 17.7% to 6.2%. These are placement figures rather than the benchmark's primary tested metric, so they are reported here as data points for further inspection rather than as a confirmed category-level shift.

Upsolve's valid recommendation count moved from 81 in July to 76 in August, a smaller change than the placement figures suggest. The brand remained visible in close to 90% of qualified observations; the larger movement is in how often it appeared at the top of the list specifically.

Highest-priority diagnostic: Which prompt types are associated with Upsolve's lower top-three and rank-one rates in August, and which brand or brands appear in those top positions instead.

Cibik Law: Entering the Public Benchmark

Cibik Law recorded its first valid recommendations in August, reaching 1.4% coverage after a 0.0% baseline in July. The brand was present in only 2 of 146 qualified observations, both positive, with 2 top-three placements and no rank-one appearances.

This move stayed within the category's normal month-to-month range for a brand at this observation count, so it is best read as an early data point rather than a confirmed trend; a single additional recommendation would materially change the brand's coverage rate.

The distinction to notice: Cibik Law's entry combines presence and recommendation together — the two new observations were both counted as valid recommendations, not just brand mentions.

Highest-priority diagnostic: Which prompts produced the two recommendations, and which surfaces or sources introduced Cibik Law into the answer set.

John T. Orcutt and Sasser Law Firm: Parallel Declines From the Second Tier

John T. Orcutt and Sasser Law Firm both fell 1.6 points from 4.3% in July to 2.7% in August, though neither movement crossed the category's threshold for a meaningful move. John T. Orcutt's top-three rate dropped from 4.3% to 2.7% (6 to 4 observations), while Sasser Law Firm's top-three rate held relatively steady, down just 0.1 points from 2.8% to 2.7% (4 to 4 observations).

Sasser Law Firm's raw presence fell more sharply, down 2.3 points from 5.0% to 2.7%, even as its rank-one rate stayed near stable. John T. Orcutt's raw presence declined roughly 0.9 points from 4.3% to 3.4%.

The distinction to notice: Sasser Law Firm lost visibility across the board but held its placement quality, while John T. Orcutt lost recommendation presence directly. Both remain tied at 2.7% coverage, sharing the second position behind Upsolve.

Highest-priority diagnostic: Whether the shared decline reflects the same prompt set or different surface dynamics for each firm, and which competitor absorbed the lost recommendations.

Buyer-Intent Interpretation

In August 2026, all 146 qualified observations fell into the Brand Recommendation cluster. None of the qualified observations fell into the Pricing & Value or Multi-Brand Comparison clusters, so the public benchmark cannot yet answer questions about pricing associations or head-to-head comparisons. The qualified set is entirely built on direct recommendation queries, which favors established, frequently named providers and does not capture the cost-conscious or comparative segments of the bankruptcy-intent journey.

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

• Small-count movement: several brands operate at 0.0% to 2.7% coverage, where a single recommendation shifts the rate by more than a point. Cibik Law's 1.4% entry reflects 2 observations; treat these as directional, not definitive.
• Qualified denominator vs raw collection: coverage percentages are calculated against the 146 qualified observations in August, not the 385 raw prompts collected. The denominator grew by 5 observations from July.
• Directional analysis: month-over-month movement identifies changes worth investigating. It does not by itself establish the cause of those changes.

Next Step

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

Beneath the aggregate percentages sit questions the public benchmark cannot answer at a brand level: which high-intent prompts are won, which competitor takes the recommendation when a brand loses, what attributes AI systems associate with each option, and which external sources shape those answers. For a leader like Upsolve, the lower top-three placement rate in August raises the question of which prompt categories and evidence sources are associated with that figure. For brands at or near zero coverage, the question is whether the absence is a visibility gap or a source-citation gap.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It tells a firm not just where it stands, but what to change and in what order.

Request an AI visibility audit