AI search optimization

How it works

AI answers are built from pages an engine can crawl and has judged worth citing. Google is blunt about the mechanics: a page has to be indexed and eligible to be shown in Google Search with a snippet before it can appear in AI Overviews or AI Mode, and there is “no special schema.org markup you need to add.” Tricks people chase, llms.txt files, keyword-specific rewrites, and artificial brand mentions, do not move the needle and can trip spam policies.

So the levers are ordinary SEO fundamentals pointed at a new output. Be crawlable to AI crawlers, earn snippet-eligible indexing, and publish unique, first-hand content instead of commodity rewrites. The academic side backs this up. In the KDD 2024 paper that coined “generative engine optimization,” Aggarwal and colleagues found that adding citations, quotations, and statistics raised a source’s visibility in generative responses by up to 40%, with the effect swinging by topic.

The term is contested. Some practitioners (Dejan Petrovic among them) argue AI search optimization is SEO under a new label, since AI engines retrieve and rank using the same signals. Either way, the work is the same: make pages a machine can find, trust, and lift a clean passage from.