AI SEO Statistics: Civil Litigation (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same civil litigation questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 80% (Claude) down to 47.5% (Gemini), a 33-point gap on an identical question set.

Across the 40 civil litigation answers it produced, ChatGPT recommended hiring a professional in 75% of them and suggested a DIY approach first 30% of the time. It named a specific provider in 5% of answers (about 0.2 distinct providers per answer) and included price or cost information 12.5% of the time. ChatGPT asked a clarifying question before answering in 77.5% of cases, warned about red flags or scams in 10%, and told the buyer to verify credentials in 15%, averaging 567 words per answer. On the remaining cues it told the buyer to check reviews in 12.5%, pointed to case studies or a portfolio in 12.5%, and framed the choice around local proximity in 37.5%; a selection-criteria checklist appeared in 30% of its answers and a recommendation to gather multiple quotes in 10%.

Across the 40 civil litigation answers it produced, Claude recommended hiring a professional in 80% of them and suggested a DIY approach first 25% of the time. It named a specific provider in 5% of answers (about 0.3 distinct providers per answer) and included price or cost information 27.5% of the time. Claude asked a clarifying question before answering in 60% of cases, warned about red flags or scams in 5%, and told the buyer to verify credentials in 5%, averaging 313 words per answer. On the remaining cues it told the buyer to check reviews in 5%, pointed to case studies or a portfolio in 5%, and framed the choice around local proximity in 37.5%; a selection-criteria checklist appeared in 25% of its answers and a recommendation to gather multiple quotes in 12.5%.

Across the 40 civil litigation answers it produced, Gemini recommended hiring a professional in 47.5% of them and suggested a DIY approach first 15% of the time. It named a specific provider in 10% of answers (about 0.4 distinct providers per answer) and included price or cost information 22.5% of the time. Gemini asked a clarifying question before answering in 2.5% of cases, warned about red flags or scams in 7.5%, and told the buyer to verify credentials in 7.5%, averaging 272 words per answer. On the remaining cues it told the buyer to check reviews in 2.5%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 27.5%; a selection-criteria checklist appeared in 17.5% of its answers and a recommendation to gather multiple quotes in 2.5%.

Taken together, Claude is the assistant most likely to route a civil litigation buyer to a professional (80%) and Gemini the least (47.5%). ChatGPT produced the longest answers, at 567 words on average. Specific providers were named most often by Gemini (10%) — even there, roughly one answer in 10 carried a name.

On other behaviors the three models move almost in lockstep — the points of near-consensus for civil litigation, where all three landed within a few points of each other:

• Names a specific provider: 5%–10% across all three (a 5-point spread).
• Warns about red flags or scams: 5%–10% across all three (a 5-point spread).
• Tells the buyer to check reviews: 2.5%–12.5% across all three (a 10-point spread).
• Tells the buyer to verify credentials: 5%–15% across all three (a 10-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "names a specific provider" (identical coding in 92.5% of questions) and least consistently on "asks a clarifying question" (15%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the civil litigation buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 6.7% of answers on average. Verifying credentials or certifications appeared in 9.2%. Warning about red flags or scams appeared in 7.5%.

On structuring the decision, a selection-criteria checklist showed up in 24.2% of answers on average and a recommendation to gather multiple quotes in 8.3%. The single least-reproduced protective signal for civil litigation is "tells the buyer to check reviews" at 6.7% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 40 questions behind every percentage on this page were drawn from real civil litigation (legal services; buyer hiring decisions for this specific service) buyer journeys. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact civil litigation question set — not a general prior or a hand-picked subset. The full list is shown earlier on this page; the coded percentages are what those specific questions produced.