AI SEO Statistics: Adult Industry (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same adult industry questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 32.5% (ChatGPT) down to 10% (Claude), a 23-point gap on an identical question set.

Across the 40 adult industry answers it produced, ChatGPT recommended hiring a professional in 32.5% of them and suggested a DIY approach first 12.5% of the time. It named a specific provider in 22.5% of answers (about 0.9 distinct providers per answer) and included price or cost information 10% of the time. ChatGPT asked a clarifying question before answering in 57.5% of cases, warned about red flags or scams in 27.5%, and told the buyer to verify credentials in 27.5%, averaging 472 words per answer. On the remaining cues it told the buyer to check reviews in 27.5%, pointed to case studies or a portfolio in 5%, and framed the choice around local proximity in 25%; a selection-criteria checklist appeared in 27.5% of its answers and a recommendation to gather multiple quotes in 2.5%.

Across the 40 adult industry answers it produced, Claude recommended hiring a professional in 10% of them and suggested a DIY approach first 5% of the time. It named a specific provider in 12.5% of answers (about 0.3 distinct providers per answer) and included price or cost information 12.5% of the time. Claude asked a clarifying question before answering in 80% of cases, warned about red flags or scams in 37.5%, and told the buyer to verify credentials in 20%, averaging 238 words per answer. On the remaining cues it told the buyer to check reviews in 27.5%, pointed to case studies or a portfolio in 5%, and framed the choice around local proximity in 22.5%; a selection-criteria checklist appeared in 30% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 40 adult industry answers it produced, Gemini recommended hiring a professional in 22.5% of them and suggested a DIY approach first 7.5% of the time. It named a specific provider in 27.5% of answers (about 1 distinct providers per answer) and included price or cost information 20% of the time. Gemini asked a clarifying question before answering in 2.5% of cases, warned about red flags or scams in 22.5%, and told the buyer to verify credentials in 5%, averaging 269 words per answer. On the remaining cues it told the buyer to check reviews in 7.5%, pointed to case studies or a portfolio in 2.5%, and framed the choice around local proximity in 7.5%; a selection-criteria checklist appeared in 27.5% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route an adult industry buyer to a professional (32.5%) and Claude the least (10%). ChatGPT produced the longest answers, at 472 words on average. Specific providers were named most often by Gemini (27.5%) — even there, roughly one answer in 4 carried a name.

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

• Mentions case studies or portfolio: 2.5%–5% across all three (a 3-point spread).
• Gives selection criteria: 27.5%–30% across all three (a 3-point spread).
• Recommends multiple quotes: 0%–2.5% across all three (a 3-point spread).
• Suggests a DIY approach first: 5%–12.5% across all three (a 8-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "recommends multiple quotes" (identical coding in 97.5% of questions) and least consistently on "asks a clarifying question" (7.5%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the adult industry buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 20.8% of answers on average. Verifying credentials or certifications appeared in 17.5%. Warning about red flags or scams appeared in 29.2%.

On structuring the decision, a selection-criteria checklist showed up in 28.3% of answers on average and a recommendation to gather multiple quotes in 0.8%. The single least-reproduced protective signal for adult industry is "recommends multiple quotes" at 0.8% 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 adult industry (professional 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 adult industry 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.