AI-search readiness can feel like an open-ended problem with no clear starting point. In practice, it breaks down into a fairly disciplined sequence — audit, structure, then test and iterate. This is the phased approach we run with clients.

Days 1–30: Audit and foundation

  1. Pick your five to ten highest-intent pages — the ones that answer the questions your best customers actually ask before buying.
  2. Test extractability. For each page, ask: if an AI model read only this page, could it state your core claim in one clean sentence? If not, rewrite the key claim to be direct and specific.
  3. Find and fix inconsistencies. Check pricing, positioning language, and key facts across your site, your social profiles, and any directories you're listed in. Contradictions make models cautious about citing you at all.
  4. Build a real FAQ layer on your most important pages — genuine buyer questions, answered plainly, not a marketing FAQ that dodges the question.

Days 31–60: Structure and authority

  1. Add structured data markup (schema.org) where relevant — organization, product, FAQ, and article schema all help systems parse your content more confidently.
  2. Pursue third-party corroboration. A claim that only exists on your own domain carries less weight than one echoed elsewhere — press coverage, industry roundups, credible directories, guest contributions.
  3. Build topical depth pages around the specific questions your buyers ask, rather than relying on one broad page to cover everything.
  4. Tighten technical fundamentals — site speed and crawlability still matter at the retrieval stage, even though they're not the whole story anymore.

Days 61–90: Test and monitor

  1. Directly test your own key queries in ChatGPT, Gemini, and Perplexity. Are you named? Is the information accurate? Is a competitor named instead?
  2. Track what analytics you can. Referral traffic from AI platforms is starting to show up as a distinct source in most analytics tools — it's imperfect, but it's a real signal worth watching.
  3. Iterate on what isn't working. If a competitor consistently gets cited over you for a specific question, look at what their content does differently — structure, specificity, or corroboration are the usual gaps.

What happens after day 90

This isn't a project with a finish line. The systems keep evolving, competitors keep publishing, and the trust signals that got you cited today need to be maintained. But 90 days is enough to move from having no intentional AI-search presence to having a real, testable one — and to know concretely what to fix next instead of guessing.

The goal of the first 90 days isn't to win every query. It's to stop being invisible on the ones that matter most.

Not convinced this deserves the effort yet? Start with the real cost of being invisible to AI search.