AI SEO Checklist

Strip away the hype and optimizing for AI search is three layers of work, each building on the last. Layer one: be retrievable. This is standard technical SEO — crawlable pages, a truthful sitemap, robots.txt rules that let AI crawlers in, server-rendered content. Most AI crawlers don't execute JavaScript and every one of them obeys (or at least reads) the same discovery infrastructure classic search uses. If GPTBot's search sibling can't fetch your page, nothing else on this checklist matters. Roughly 80% of "AI SEO" is this layer, which is why agencies selling it as an exotic new discipline are mostly reselling technical SEO audits.

Layer two: be resolvable. AI systems answer questions about entities — brands, people, products — and they need to be certain your site, your LinkedIn page and the reviews on G2 all describe the same thing. Organization and Person schema with sameAs links, one canonical brand-name spelling, and a factual About page are how you become one unambiguous node in the knowledge graphs these systems consult. Skip this layer and your mentions get split with every same-named company on the internet.

Layer three: be citable. This is the genuinely new part. AI search retrieves passages, not pages, so sections need to answer their own heading in the first sentence and stay compact — roughly 75–300 words. And the content itself matters: the Princeton GEO study (KDD 2024) measured which tactics raise a page's odds of being used in generated answers, and the winners were concrete statistics, quotations and cited sources — up to 30–40% more generative-engine visibility. The same research found keyword stuffing does nothing or hurts. Write like a source, not like a landing page.

Plenty of AI-SEO checklists pad themselves with items that sound current but are verifiably dead or unproven, so it's worth saying what this one treats honestly. FAQ rich results are gone — Google deprecated them for all sites in May 2026, so no checklist item here promises them; the FAQ format stays on the list because assistants quote visible Q&A text nearly verbatim. llms.txt is a hedge, not a tactic — no major engine has confirmed consuming it and Ahrefs found 97% of published files get zero AI-crawler requests, so it appears here as a low-effort, low-impact item, exactly what it is. Blocking Google-Extended does not remove you from AI Overviews — it only governs Gemini training, a distinction half the guides on this topic get wrong. And meta descriptions are not how AI reads your page — engines summarize actual content, which is why the checklist points you at your opening paragraph instead.

The prioritization logic is equally plain: impact first, quick wins early when you're starting from zero, and categories reordered around your stated goal — being recommended leans on content and entity work, protecting accuracy leans on monitoring, driving referral traffic leans on crawler access.

Every other category changes what AI systems can say about you; only monitoring tells you what they actually say. Answers drift as models update, indexes refresh, and competitors publish — a brand that checked once in January can be misrepresented by June without anyone noticing. That's why the checklist starts and ends with measurement: run a baseline before you touch anything, and re-check a fixed set of real buyer prompts on a schedule afterwards, so every fix on this list is verified against reality instead of assumed to have worked. The free AI Visibility Checker gives you that baseline in about a minute — no login, real grounded-model answers, and the score to beat.