Robins Kaplan AI Market Strategy Report - Product Liability Lawyers

Answer Capsule

Robins Kaplan holds almost no recommendation-stage visibility in the product liability lawyers category. In September 2026, the firm recorded a raw mention presence rate of 0.95% and a valid recommendation coverage of 0.63%, placing it ninth of ten tracked brands. Its clearest weakness is the absence of any top-three placement in the category, and its clearest opportunity is a narrow but real recommendation pocket on ChatGPT, where it holds one valid recommendation at an average rank of 5. The benchmark shows a firm that is occasionally retrieved but almost never shortlisted.

Who This Report Is For

This report is for Robins Kaplan's marketing, business development, and executive leadership teams, and for any product liability firm that wants to understand how AI systems are shaping buyer shortlists in this category.

Report Card

Executive Summary

Robins Kaplan is visible in AI-generated answers for product liability queries, but that visibility almost never converts into a recommendation. Across 316 qualified observations in September 2026, the firm appeared in just 3 mentions, a raw mention presence rate of 0.95%. It received 2 valid recommendations, a valid recommendation coverage of 0.63%, and recorded no top-three placements and no rank-one placements in the entire benchmark.

The firm's net sentiment score of 0.67 is positive, but it rests on a sample of 3 mentions: 2 positive and 1 neutral, with no negative framing detected. That is a favorable framing signal, not a meaningful visibility position. The benchmark's own interpretation notes flag that this vertical has a smaller qualified observation base and that movements of a few percentage points can reflect a modest number of prompts.

Robins Kaplan's strongest platform signal is ChatGPT, where it holds 1 valid recommendation at an average recommended rank of 5, alongside 1 raw mention. That single recommendation is the firm's only rank-eligible placement in the category. On Perplexity, the firm holds 1 valid recommendation at an average recommended rank of 9. On Google AI Overviews, it recorded 1 neutral mention with no recommendation credit.

The clearest gap is structural rather than incremental. Robins Kaplan has zero presence on Copilot, Gemini, and Google AI Mode, and zero top-three placements on any platform. By comparison, Morgan & Morgan holds a 17.09% top-three rate and an 11.08% rank-one rate, and even ninth-place Lieff Cabraser holds a 1.27% top-three rate. Robins Kaplan is the only tracked brand other than Aylstock Witkin Kreis & Overholtz with no top-three placement at all.

The category context makes the position more urgent. The benchmark shows recommendation breadth contracting across the series, with the valid recommendation shortlist share falling from 69.0% in July 2026 to 59.8% in September 2026. A firm that is not already inside the shortlist is competing for a narrowing set of recommendation slots.

What Robins Kaplan Is Winning

Questions This Section Answers

• Where does Robins Kaplan actually hold rank-eligible recommendations in the benchmark?
• How does Robins Kaplan's sentiment compare to competitors like Motley Rice and Beasley Allen?

Robins Kaplan's evidence-backed wins are narrow, and the report states them plainly rather than overstating them.

The firm has no negative framing in the benchmark. All 3 of its mentions were classified as positive or neutral, producing a net sentiment score of 0.67. In a category where several competitors carry lower sentiment scores, including Motley Rice at 0.52 and Beasley Allen at 0.62, Robins Kaplan's framing quality is not a weakness.

The firm holds a genuine, if small, recommendation pocket on ChatGPT. That single valid recommendation at an average rank of 5 is the firm's only rank-eligible placement across all six platforms, and it indicates that at least one high-intent prompt surface will name the firm in a recommendation context.

The firm also holds one valid recommendation on Perplexity at an average rank of 9, which places it at the outer edge of the top ten rather than outside it entirely.

Beyond these three observations, the benchmark does not support additional claims about Robins Kaplan's competitive position.

Where Robins Kaplan Has the Clearest AI Visibility Gaps

Questions This Section Answers

• Why is Robins Kaplan's mention presence not converting into recommendations?
• Which AI platforms show no Robins Kaplan presence at all?
• How large is the recommendation gap between Robins Kaplan and category leaders like The Lanier Law Firm?

Robins Kaplan's central gap is that it is present without being chosen. The firm's raw mention presence rate of 0.95% and its valid recommendation coverage of 0.63% are close together, which means most of the few times it appears, it appears as context rather than as a recommendation. That is a different problem from being absent, and it points to a framing and evidence issue rather than a pure discoverability issue.

The firm has no top-three placement anywhere in the benchmark. This is the sharpest gap in its profile. Morgan & Morgan converts 17.09% of qualified observations into top-three placement and 11.08% into rank-one placement. Weitz & Luxenberg holds a 21.52% top-three rate. The Lanier Law Firm holds a 19.94% top-three rate. Even Lieff Cabraser, which sits one position above Robins Kaplan in the standings, holds a 1.27% top-three rate and a 0.32% rank-one rate. Robins Kaplan holds neither.

Three of the six tracked platforms show no Robins Kaplan presence at all. The firm recorded zero mentions on Copilot, zero on Gemini, and zero on Google AI Mode. Google AI Mode alone accounts for 86 qualified observations in the benchmark, and Copilot accounts for 40. Those are surfaces where the firm is not part of the answer set in any form.

The firm's only neutral mention in the benchmark came from Google AI Overviews, where it appeared once without recommendation credit. Google AI Overviews carries 92 qualified observations, and competitors including The Lanier Law Firm, Weitz & Luxenberg, and Morgan & Morgan hold substantial recommendation coverage there. Robins Kaplan's single neutral mention on that surface indicates it is retrievable but not recommendable in its current form.

The comparison to the category leader is stark. The Lanier Law Firm holds 95 valid recommendations and a 30.06% valid recommendation coverage. Robins Kaplan holds 2 valid recommendations and a 0.63% coverage rate. The gap is not a matter of degree within a competitive tier; it is a gap between being inside the recommendation set and being outside it.

Biggest Opportunity

Questions This Section Answers

• Which platforms offer Robins Kaplan the shortest path from reference to recommendation?
• How could the neutral mention on Google AI Overviews be converted into a valid recommendation?

Robins Kaplan's clearest path from reference to recommendation runs through ChatGPT and Perplexity, the two surfaces where it already holds rank-eligible placements.

On ChatGPT, the firm holds 1 valid recommendation at an average rank of 5. Moving that placement from rank 5 into the top three is the shortest available improvement in the entire profile, because the firm is already inside the recommendation set on that surface. On Perplexity, the firm holds 1 valid recommendation at an average rank of 9, which means it is being named at the outer boundary of the shortlist. Both surfaces represent prompts where the firm has already cleared the hardest threshold, which is being named at all.

The supporting opportunity is the neutral mention on Google AI Overviews. That surface carries the second-largest observation base in the benchmark at 92 qualified observations, and the firm currently appears there without recommendation credit. Converting a neutral reference into a valid recommendation on that surface would address the firm's largest single-platform gap.

Competitive Landscape

Questions This Section Answers

• Which firms hold the strongest recommendation-stage positions in product liability lawyers?
• How does Robins Kaplan's average recommended rank compare to other rank-eligible brands?

Morgan & Morgan, Weitz & Luxenberg, and The Lanier Law Firm hold the strongest recommendation-stage positions in the product liability lawyers category, and Robins Kaplan sits in the bottom tier with no top-three placement and no rank-one placement.

Average recommended rank covers rank-eligible recommendations only.

Robins Kaplan's row shows the position clearly: no top-three rate, no rank-one rate, and an average recommended rank of 7 across its rank-eligible placements, which is the weakest average rank of any brand in the table that holds a rank-eligible recommendation. The firm's sentiment score of 0.67 is mid-tier and rests on a very small mention count.

Prompt Evidence

ChatGPT / Best Product Liability Lawyers & Top Law Firms Prompt: "personal injury attorney" Result: Robins Kaplan holds 1 valid recommendation on ChatGPT at an average recommended rank of 5, its strongest placement in the benchmark.

Perplexity / Best Product Liability Lawyers & Top Law Firms Prompt: "personal injury lawyer near me" Result: Robins Kaplan holds 1 valid recommendation on Perplexity at an average recommended rank of 9, placing it at the outer edge of the shortlist.

Google AI Overviews / Best Product Liability Lawyers & Top Law Firms Prompt: "personal injury law firm" Result: Robins Kaplan appears once as a neutral reference with no recommendation credit, indicating retrievability without shortlist inclusion.

What CiteWorks Studio Would Do Next

Questions This Section Answers

• What does the AI Market Discovery Audit identify about Robins Kaplan's prompt-level gaps?
• Which surfaces does the Recommendation Readiness Plan prioritize for moving into the top three?

Phase 1: AI Market Discovery Audit Map the specific prompts where Robins Kaplan is retrieved but not recommended, and identify which competitors take the recommendation slot when the firm is named without credit.

Phase 2: Recommendation Readiness Plan Prioritize the ChatGPT and Perplexity placements already inside the recommendation set, and define the evidence and framing changes needed to move those placements into the top three.

Phase 3: Owned Answer Layer Buildout Build firm-controlled pages that answer the high-intent product liability prompts directly, with clear practice-area, jurisdiction, and case-type signals that AI systems can retrieve and attribute.

Phase 4: Citation / Authority Layer Development Strengthen the public evidence layer around the firm's product liability work so that third-party sources describing the firm are specific enough to support a recommendation rather than a passing reference.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track mention presence, valid recommendation coverage, top-three rate, rank-one rate, and sentiment by platform each month to confirm whether the firm is moving from reference into recommendation.

Why This Matters

AI systems are now forming the buyer shortlist before a prospective client ever visits a firm's website. In the product liability lawyers category, the benchmark shows that recommendation breadth is contracting, with the valid recommendation shortlist share falling from 69.0% in July 2026 to 59.8% in September 2026. A firm that is not inside the recommendation set is not competing for a smaller share of the shortlist; it is absent from the shortlist entirely.

Presence alone does not solve this. Robins Kaplan is mentioned in AI-generated answers, and its framing is positive, but it holds no top-three placement and no rank-one placement in the category. The next move is targeted correction of the prompt, page, and citation layers so that the firm's existing mentions convert into recommendation credit on the surfaces where it is already retrievable.

Core Metrics

Sentiment Score

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For Robins Kaplan in September 2026, that calculation is (2 × 1 + 1 × 0 + 0 × -1) / 3, which produces a sentiment score of 0.6667.

This matters because unclassified mention counts are misleading. A firm that appears in 3 AI answers could be described positively, referenced neutrally as background context, mentioned with a caution, or named only as a comparison anchor against a competitor. Those are four different outcomes, and counting them all as wins is bad measurement.

Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, a neutral reference, a cautionary mention, and a competitor-displaced mention are not equal in value to a buyer forming a shortlist. Robins Kaplan's score of 0.67 reflects a small sample of favorable mentions, and the score should be read alongside the mention count rather than on its own. Classified sentiment is required before interpreting AI visibility, and in this case the classification shows a firm with good framing and almost no recommendation footprint.

Sentiment by Platform

Methodology

1. This report is a benchmark-based analysis of Robins Kaplan's position in the product liability lawyers category, produced from the LLM Authority Index AI Market Discovery Index for September 2026. It is not a client implementation result.
2. The reporting window is September 2026, with July 2026 as the baseline month and August 2026 as the intervening measurement.
3. Six AI surface families were tracked: ChatGPT, Copilot, Gemini, Perplexity, Google AI Overviews, and Google AI Mode. All six recorded at least one qualified observation in the period.
4. The September 2026 collection began with 670 prompt-surface observations and 497 unique questions. Of those, 521 were relevant to the vertical and 149 were irrelevant, producing 316 qualified observations as the public denominator.
5. Ten brands were tracked in the competitor universe: Morgan & Morgan, Aylstock Witkin Kreis & Overholtz, Baron & Budd, Beasley Allen, Lieff Cabraser, Motley Rice, Robins Kaplan, The Lanier Law Firm, Weitz & Luxenberg, and Wilshire Law Firm.
6. Three public high-intent clusters were defined: Best Product Liability Lawyers & Top Law Firms (consideration stage), Product Liability Lawyer Comparisons & Firm Evaluations (evaluation stage), and Product Liability Lawyer Fees, Costs & Pricing (decision stage).
7. All 316 qualified observations in September 2026 fell into the Brand Recommendation cluster. The comparison and pricing clusters recorded zero observations, so this report cannot address how AI systems characterize firms on price, value, or head-to-head comparison.
8. A mention is counted when a tracked brand appears in an AI-generated answer in any context, including neutral reference and comparison anchoring.
9. A valid recommendation is counted only when the dataset marks the brand as receiving a recommendation. Neutral, cautionary, and listed-only mentions are not counted as valid recommendations.
10. Average recommended rank covers rank-eligible recommendations only. Robins Kaplan's average recommended rank of 7.00 is calculated from its rank-eligible placements and should be read alongside its very small recommendation count.
11. The qualified denominator of 316 is smaller than the raw collection of 670. Brand-level percentages are calculated within the qualified set only, and this vertical carries a smaller qualified observation base than larger categories tracked in the index.
12. Month-over-month movement identifies changes worth investigating; it does not by itself establish why those changes occurred. The benchmark records the output distribution, not its underlying cause.

See Where AI Is Recommending Your Brand

The public benchmark shows where a firm stands in AI-generated recommendations. A company-level AI visibility audit maps the specific prompts, competitors, surfaces, and evidence sources behind that position, and turns them into a prioritized plan for moving from reference into recommendation.