Evidence Architecture for AI Search: What a Vancouver Service Page Actually Needs
Pause when someone promises that an “AI schema” block will earn placement in AI Overviews. Google Search Central says AI Overviews and AI Mode have no additional technical requirement, special schema, or new machine-readable file. A page must still be indexable and eligible to show a snippet, while meeting the existing search and content-quality foundations.
Evidence architecture makes a claim verifiable
AI search can break a question into related subqueries and synthesize across sources. A page that says only “innovative, tailored, industry-leading solutions” offers no extractable evidence. Give a service page six parts:
- Definition: what the service does, does not do, and who it fits.
- Scope: cities, industries, languages, deliverables, and timing.
- Method: real steps, decision points, and client inputs.
- Price context: a starting point, range, or cost variables.
- Evidence: dated cases, outcomes, limitations, credentials, and primary sources.
- Questions: direct answers about comparison, risk, and next action.
Align page copy, schema, and external records
| Layer | Information | Test |
|---|---|---|
| Visible page | Name, service, geography, author, date, sources | A reader can find it without viewing source |
| Structured data | Applicable Article, Organization, Breadcrumb, and FAQ types | Every value agrees with visible content |
| External entity records | Business Profile, social accounts, professional directories | Name, URL, services, and contact details are consistent |
Schema describes content already present; it should not make claims the page does not. Google’s guidance specifically calls for structured data to match visible text, important information to remain textual, and pages to be discoverable through internal links.
Write citable sections without writing for a robot
Let each section answer one question, then add conditions, an example, and a source. Use a table for a comparison, numbered steps for a process, and FAQ for short decisions. Do not turn the article into a flat dictionary in the hope of extraction. First-hand cases, expert judgment, and disclosed limitations are the parts a generic model cannot reproduce.
Start with our GEO 101 guide; use this article to audit the evidence on a service page.
A quarterly GEO audit
- Confirm that core pages remain indexable, canonicals are correct, and key information is present in HTML text.
- Update expired figures, case dates, service areas, and team credentials.
- Repair orphan pages with useful links from services, cases, and related articles.
- Review Search Console queries and conversions; do not treat one AI-answer screenshot as a ranking report.
Frequently asked questions
Is llms.txt required for Google AI search?
No. Google Search Central says no new machine-readable files are required. Eligibility still depends on indexing, snippet availability, and the established Search foundations.
Does FAQ schema improve rankings?
Structured data is not a ranking guarantee. It should accurately describe a visible FAQ; Google determines whether a search feature is shown.
How should AI-search performance be measured?
Google includes traffic from AI features in Search Console’s Web search type. Pair it with enquiry source, branded demand, and conversion quality rather than sessions alone.
Sources and scope
Technical claims follow Google Search Central’s 2025–2026 AI-features documentation. Other search and answer products may use different systems, and no eligible page is guaranteed indexing or citation.