AI-search readiness begins with clear, accessible and supportable information. The useful audit connects each buyer claim to evidence, discovery and ownership.
Audit the proof path, not an AI score
An AI-search audit should answer a practical question: can a search system find a page that states what your business does, understand the claim in context and connect it to evidence a buyer can assess? The audit cannot promise inclusion in an AI answer. It can remove ambiguity and unsupported copy that makes the business harder to evaluate.
Google's current guidance says the established foundations of SEO still apply to its generative search features. A page must be indexed and eligible to appear with a snippet, and no special AI text file or schema is required. Google also requires the site to be included in generative AI features through Search Console. Meeting these conditions does not guarantee display. See Google's guide to generative AI features.
That boundary matters. Do not replace evidence with an “AI visibility score” built from undocumented prompts. Record what was checked, where, when and under which product conditions. Treat observed citations as observations that can change, not as a durable ranking.
Inventory the claims a buyer needs to trust
Start with the decisions a buyer must make. They may need to know who the service is for, which problem it covers, what is delivered, what is excluded, where it is available and what evidence supports a result claim. List those claims before reviewing markup or crawler settings.
Classify each item as verified fact, supported interpretation, proposal or unsupported assertion. A verified fact should point to a current business record or authoritative external source. A supported interpretation should show the inputs and reasoning. A proposal should be labelled as future work. Remove an unsupported assertion or assign the work needed to support it.
Google's people-first content guidance asks whether content provides original information, substantial value and clear sourcing. That guidance does not create a checklist that guarantees visibility. It does reinforce the editorial question: would this page help the intended reader even if search traffic were removed from the equation?
Build an evidence-to-page map
| Field | Audit question |
|---|---|
| Claim | What exactly is the business asking a buyer to believe? |
| Support | Which current record or primary source supports it? |
| Visible page | Where can a reader find the claim and its necessary context? |
| Eligibility | Can the page be crawled, indexed and shown with a snippet? |
| Discovery path | Which relevant page links to it? |
| Structured-data match | Does markup describe the visible content accurately? |
| Owner and date | Who rechecks the fact, and when? |
| Gap | What remains unsupported, inaccessible or ambiguous? |
This map separates content work from technical work. A true claim hidden in a private sales deck needs a public explanation if it is important to search. A clear public explanation blocked from indexing needs a technical review. Valid structured data cannot rescue an unsupported claim.
Make important evidence readable in context
Put essential facts in accessible page text. Images can illustrate an idea, but text inside an image should not carry the only explanation of a service, price condition or limitation. Give tables clear headings, give images descriptive alternative text and use links whose labels explain the destination.
Write claims at the level the evidence supports. “Works with subscription apps that can identify a first-value event” is a useful constraint when the service genuinely has that scope. “The best growth partner for every app” is neither specific nor supportable. Specific boundaries help both readers and retrieval systems understand relevance.
Internal links should reflect the relationship between pages. A method article can link to the service that applies it. A service page can link to a detailed explanation when a buyer needs the method. Avoid building dozens of near-identical pages whose only purpose is to repeat a city or industry name.
Check discovery, indexing and representation
For every priority page, verify that normal navigation reaches it, the server returns the intended status, robots rules allow the desired search access and the canonical URL is correct. Use Search Console's URL Inspection tools and indexing reports where access is available. Record the observed state and date rather than assuming that a sitemap entry proves indexing.
Compare structured data with visible content. Google's structured-data guidance describes supported search appearances. Matching markup can help establish eligibility, but appearance is not guaranteed. Use a type that fits the visible page and do not add ratings, authorship or business facts that readers cannot verify on the page.
Separate search access from other crawler policies. Different products and user-initiated fetchers can use different agents. A permissive rule does not guarantee citation, and a citation observed in one product does not describe every AI system.
Turn unsupported claims into a correction queue
A software company calls its onboarding platform “the fastest in the market.” It has no comparative study. The audit removes the superlative. Product records do confirm that administrators can import a CSV, invite reviewers and export an approval log. The page is rewritten to state those functions and adds the documented file and role limits. This is more useful to a buyer and easier to verify.
The example does not suggest that detailed copy automatically earns an AI citation. It shows how the audit improves the information available for evaluation. Put each unsupported claim into one of four queues: verify, narrow, label as a proposal or remove.
Assign an owner and source for volatile facts such as availability, platform support or pricing. A page that was accurate at publication can become misleading. Freshness is a maintenance responsibility, not a date badge added without review.
Test whether a reader can verify the answer path
Choose three questions a qualified buyer is likely to ask and try to answer them using only public pages. For each question, record the page where the answer begins, the supporting source, the necessary limitation and the next relevant page. Ask someone unfamiliar with the site to repeat the task. Confusion is an editorial finding even when the technical markup is valid.
Failure patterns are often simple. A claim may exist only in a PDF that navigation never reaches. A service page may use a category label without explaining the deliverable. A statistic may link to a secondary article that cites no original study. A pricing statement may omit the region or effective date needed to interpret it.
Correct the shortest broken link in the evidence chain. Add the missing context to the visible page, replace a weak citation with the primary source, or remove a statement that cannot be supported. Do not create a special “AI version” that says something different from the page buyers see.
Measure what the available tools can show
Google's current generative AI guidance points to a Generative AI performance report in Search Console. Check the report available to your property and its documented scope before drawing conclusions. It is not a universal citation report across other companies' AI products. Record page and query changes with the same country, device and date filters used for the baseline.
For other search assistants, a bounded manual observation can record the prompt, account state, location where known, date and cited sources. Repeat the same observation carefully, but do not turn a small sample into market share. Product behavior can change without notice.
Finish the audit with a correction queue, technical findings and unresolved evidence gaps. The outcome is a clearer and more supportable website. Later observation can assess whether search visibility changes. For help with the underlying content and search structure, see MORE's SEO service.
