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Research

AI search research — what the evidence actually says

AI search attracts confident claims and very little evidence. This page collects the sources we rely on, labelled by type, so you can see what is documented by platforms, what independent researchers have measured, and what is our own interpretation.

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By · Updated · 2 min read

How to read this page

Every source is labelled:

  • Platform documentation — what a vendor says about its own product. Authoritative on mechanics; not independent.
  • Independent research — measurements by third parties with published methods.
  • Academic research — peer-reviewed or preprint studies.
  • Prisol analysis — our own interpretation or data. Always marked, never presented as independent.

Platform documentation

Source What it establishes Our note
Google Search Central — AI features and your website AI Overviews and AI Mode have no extra eligibility requirements beyond being indexed and snippet-eligible; may use query fan-out; clicks are reported in Search Console under Web The most direct guidance any platform has published. Undercuts claims that special markup or files are needed.
Google — common crawlers (Google-Extended) Google-Extended controls Gemini training and grounding; does not affect Google Search inclusion Important for robots.txt decisions.
OpenAI — crawlers OAI-SearchBot (search), GPTBot (training), ChatGPT-User (user fetches) serve different purposes Blocking GPTBot does not remove you from ChatGPT search.
Perplexity — crawlers PerplexityBot surfaces sites in results and is not used for training; Perplexity-User handles user-initiated fetches Allow PerplexityBot for citations.
Bing Webmaster Tools — AI Performance report (public preview, 2026) Reports citation counts for your pages in Copilot and Bing AI answers Rare first-party AI citation data; no click data.

Independent research

Source Finding Our note
Pew Research Center, July 2025 — browsing data from 900 U.S. adults, 68,879 Google searches, March 2025 Traditional result clicked in 8% of visits with an AI summary vs 15% without; links inside summaries clicked in 1%; sessions ended more often after a summary (26% vs 16%) Strong method (real browsing data). U.S.-only, one month, Google only. Google disputed the methodology.

Academic research

Source Finding Our note
Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan & Deshpande, GEO: Generative Engine Optimization (arXiv 2311.09735, 2023; KDD 2024) Introduced the term GEO and a benchmark; found that content changes such as adding citations, quotations and statistics could increase a source’s visibility in generative engine responses Tested on research systems, not on commercial products’ current versions. Useful directional evidence that clear, evidenced content helps.

Prisol analysis

We have not yet published original research. Planned work will follow these standards:

  1. Methods published in full: prompts, platforms, dates, locations, run counts, coding rules.
  2. Sample sizes and limitations stated alongside every number.
  3. No claims about platform internals that the data can’t support.
  4. Raw data shared where client confidentiality allows.

Claims we treat with caution

  • Precise “AI ranking factors” or percentages from vendors without published methods.
  • Single-screenshot evidence of visibility.
  • Claims that any file, markup or tool guarantees inclusion in AI answers.

FAQ

Research: frequently asked questions

Why doesn't Prisol publish its own AI visibility statistics?
We will only publish research with a sound, disclosed method and adequate sample. Until then we'd rather cite others' evidence clearly than publish numbers we can't stand behind.
How do you choose which studies to include?
We prefer primary sources — platform documentation, peer-reviewed or preprint research, and independent studies with published methods. Vendor marketing claims without methods are excluded.
Can I suggest a study?
Yes. Email us with a link to the primary source and its methodology.

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