An AI search readiness checklist you can work through with evidence

A useful readiness review ends with decisions you can act on: which page needs attention, what evidence supports the change and how you will know it worked. Start with a small, representative sample rather than treating a single homepage score as a verdict on the entire business. This checklist is a working method you can adapt to a service site, publication or product documentation library.

1. Define the question before collecting a score

Write down the audience, the task they need to complete and the page that should help them. “Can a prospective customer understand our reporting service?” is a workable question. “Are we optimized for every AI?” leaves you without a clear test. Choose one priority question and identify the page you would want a reader to reach.

Keep technical readiness separate from observed answer results. Google says its AI Overviews and AI Mode use the same foundational search requirements, with no additional special markup or machine file required. Eligibility still does not guarantee inclusion. Google’s AI features guidance is the starting reference; our readiness versus visibility explainer describes the measurement boundary.

2. Choose pages that represent different jobs

Select an entry page, a detailed answer or service page and an identity or contact page. Record why each belongs in the sample. If the site also has product pages, location pages or member-only material, list those as separate shapes for a later review. Three accessible pages cannot prove that every route or template works.

• Entry page: what is this organization and what does it offer?
• Detailed page: does it answer one useful question with enough context?
• Identity page: can a visitor establish who is responsible and how to contact them?

Write down the exact URLs and the check time. Preserve the response status and final destination after redirects. If a page was unavailable, leave its content assessment unknown; do not award it a zero for facts you could not inspect.

3. Establish access before rewriting content

Open each URL in a clean browser and retrieve its initial HTML. Confirm you received the expected page rather than a login screen, challenge or soft error. Review robots rules, response headers and page-level indexing directives together. A public answer page and an account area should not inherit the same access decision by accident.

Use our crawler access procedure to isolate the layer causing a block. Changing copy while the page remains inaccessible does not address that particular problem. Preserve deliberate restrictions on private routes and record the intended public canonical before altering redirects or indexing rules.

4. Make the page’s identity unambiguous

Read the title, heading, introductory paragraph and canonical as one package. Do they identify the same subject and destination? A page called “Solutions” may need a more specific title when it actually explains an inventory reporting service. Describe the real service; do not add claims about leadership, results or certifications that the page cannot support.

Check internal links next. Can someone reach this detailed page from the relevant parent section? Can they continue to a useful next step? Prefer descriptive link text that tells the reader what they will find. For example, link a schema troubleshooting paragraph to the actual checking guide rather than placing an unrelated collection of network links below every article.

5. Check facts and markup together

Create two short columns: visible fact and matching structured field. Compare the real publisher, author, dates and subject with the emitted JSON-LD. Leave unknown details out. A valid JSON object can still describe the wrong organization or an article that has never been written.

CheckMySchema can help inspect the markup, and its Machine Interface describes local and hosted checking routes. Follow the structured data validation workflow for the separate syntax, vocabulary and visible-content checks.

6. Produce a small action list and repeat the same check

For each finding, capture the affected URL, observation, intended change, owner and verification. Start with an inaccessible public page or wrong canonical, then improve clarity and evidence. Keep optional refinements separate so a missing decorative image does not displace a genuine access failure.

After deployment, repeat the original retrieval and compare the same fields. Record what changed and what remains unknown. Then run a neutral answer observation separately, using the same question and provider context. A cleaner site is a concrete improvement; a later citation is a different outcome that needs its own evidence.