AI search is not a new discipline
Treating optimisation for AI search as a separate profession to learn from scratch is a mistake. Google says its AI search features still run on its core ranking systems. There is no standalone 'AI optimisation' to bolt on. The ordinary requirements for a site have not gone anywhere.
In practice the content still has to be crawlable, indexable and useful. A site closed to bots, pages missing from the index, or copy written for a search engine rather than a reader will not be rescued by work aimed at AI search.
The basics AI search does not replace
Three things to check before thinking about new formats. Crawler access: robots.txt, server response time, no blocks on important sections. Indexability: canonical tags, correct redirects, a sitemap without broken links. Content value: does the page answer the user's query or just collect keywords. Miss any one and the rest loses its point.
Microsoft says much the same — its search AI features also rely on existing search infrastructure. Neither company has confirmed separate requirements for AI features, so there is no race for 'AI factors'.
For an affiliate or media buyer this means the funnel does not collapse. A landing page that ranks well and answers intent is likely to be picked up by AI features too. What is worth rechecking: whether an anti-detect browser or CDN is cutting off search bots and serving them a captcha or an empty page, and whether pages are templated copies that add nothing to what already ranks. Split material with subheadings and put the direct answer in the first paragraph of a section rather than at the end of a long read.
Spinning up 'special pages for AI' and waiting for results is not the move. Money spent on crawling quality and content returns in both classic SEO and AI search. That suits anyone who has already invested in SEO. The strategy stays; close the technical gaps first, then fix the pages that fail to answer a query.
