# AI Search Visibility: Readiness, Visibility Potential, Observed Visibility & Competitor Comparison AISearch.wiki is an independent reference and diagnostic site for AI search visibility. It separates three questions that should not be collapsed into one score: 1. **AI Search Readiness** — Can search and AI systems technically reach and interpret the page? 2. **AI Visibility Potential** — Does the page contain strong public signals for discoverability, entity clarity, evidence, answer extraction, trust and freshness? 3. **Observed AI Visibility** — Does the brand or domain actually appear, get mentioned or get cited for a defined set of prompts at a defined time? The **Observed AI Visibility Checker + Competitor Comparison** also compares tracked brands across the same prompt set so users can see who surfaces more often, who gets cited, and where visibility gaps exist. Last updated: 2026-09-10. ## Primary Tools - [Observed AI Visibility Checker + Competitor Comparison](https://www.aisearch.wiki/tools/observed-ai-visibility-checker/) — Observe brand mentions, domain citations, prompt coverage and tracked competitor share of voice across configured AI answer providers. - [AI Visibility Potential Checker](https://www.aisearch.wiki/tools/ai-visibility-checker/) — Inspect discoverability, entity strength, citation/source strength, answer extractability, trust and freshness. - [AI Search Readiness Checker](https://www.aisearch.wiki/tools/ai-search-readiness-checker/) — Inspect crawlability, indexability, canonicalization, sitemap discovery, structured data, headings, authorship and other technical foundations. ## Check → Compare → Fix → Recheck **Check:** Establish an observed baseline using a defined prompt set and provider set. **Compare:** Track the same prompts for relevant competitors and identify differences in mentions, citations and share of voice. **Fix:** Use the Readiness and Visibility Potential diagnostics to investigate likely technical, entity, evidence, content and trust gaps. **Recheck:** Repeat the same observation framework after meaningful changes and compare results against the baseline. ## What Observed AI Visibility Means Observed AI visibility is evidence from a specific observation. It is not a permanent universal ranking. Results can vary by provider, query, locale, personalization, time, source selection and product behavior. A useful observed report should record: - prompt tested; - provider or answer system; - date/time; - whether the target brand was mentioned; - whether the target domain was cited or returned as a source; - which tracked competitors surfaced; - which sources were returned; - change from the prior or baseline observation when historical tracking is available. ## What Competitor Comparison Means Competitor comparison applies the same prompt set and observation method to the target and explicitly tracked competitors. It is useful for identifying: - prompts where a competitor appears and the target does not; - citation gaps; - differences in mention coverage; - approximate share of voice within the tracked set; - changes after the target or a competitor publishes new material. Competitor comparison should not be described as a universal AI ranking because AI answer systems vary by prompt, time, location and provider. ## AI Search Readiness AI Search Readiness asks whether a page is technically prepared to be found and interpreted. Important checks include: - valid HTTP/HTTPS response; - indexability; - canonicalization; - sitemap discovery; - robots and crawler access; - titles and headings; - crawlable textual content; - structured data; - visible authorship and responsibility; - visible source and date signals. ## AI Visibility Potential AI Visibility Potential asks whether a page has public signals that can make it easier to understand, trust and cite. AISearch.wiki evaluates categories such as: - discoverability; - entity strength; - citation/source strength; - answer extractability; - trust and freshness. A high potential score does **not** guarantee a mention or citation. ## AI Search Optimization Framework ### Discover Make important pages crawlable, indexable, internally linked and technically stable. ### Understand Use descriptive headings, clear entity naming, semantic HTML and accurate structured data that matches visible content. ### Trust Show evidence, sources, authorship, methodology, original analysis and update dates when relevant. ### Cite Write self-contained answer passages that directly answer identifiable questions and provide a reason for the page to be used as a source. ### Observe Test defined prompts and record what actually surfaces. ### Improve Use observed gaps to guide technical, entity, evidence and content improvements, then retest. ## Platform Guidance Google states that its existing SEO best practices remain relevant for AI Overviews and AI Mode and that there are no special additional technical requirements solely for those AI features. OpenAI states that publishers who want content to be discoverable for ChatGPT search summaries and citations should not block OAI-SearchBot. AISearch.wiki treats `llms.txt` as an optional publishing convention, not as a guaranteed ranking directive. ## Primary References - [Google Search Central — AI features and your website](https://developers.google.com/search/docs/appearance/ai-features) - [OpenAI — Publishers and Developers FAQ](https://help.openai.com/en/articles/12627856-publishers-and-developers-faq) - [Schema.org — WebApplication](https://schema.org/WebApplication) ## Limitations AISearch.wiki does not claim to reverse-engineer proprietary ranking systems. Readiness scores, visibility-potential scores, observed scans and competitor comparisons are diagnostic evidence. They do not guarantee rankings, recommendations, mentions or citations.