What is AI search

AI search defined for marketers

For marketers, AI search is a channel where the answer either names your brand or leaves it out. Users rarely see your page first. They see a summary that quotes or cites you, and they click only when they want more detail. What you compete for is a mention and a citation, where it used to be a ranking position.

AI search versus Google

AI search hands back a written answer, while classic Google Search hands back a ranked list of pages. On a results page, you compare the links and judge them yourself. An AI engine does that comparing for you and shows a few sources as footnotes. Google now runs AI Overviews and AI Mode inside its own results, so check which surface you're measuring.

How AI search works

In the first of two stages, the AI search engine turns your question into one or more queries and pulls matching pages from a search index. This method is called retrieval-augmented generation (RAG). Then the model reads those pages and writes a reply with citations. If retrieval brings back weak pages, the answer gets worse.

Why AI visibility matters

AI visibility matters because the answer ends the search. Say a buyer asks an assistant for the best tools in your category and your brand isn't named. You've lost that buyer before they reach any website. Results also differ between engines, so check each assistant your buyers actually use.

What generative search means

Generative search is the umbrella term for search that writes a new answer. It covers standalone AI engines and the AI layers inside traditional search engines. The phrase "generative engine" gave us GEO, short for generative engine optimization.

How AI engines rank sources

AI engines rank sources by how well a passage answers the query and how far the engine trusts the site behind it. No engine publishes its full method. Pages that state the answer plainly near the top receive more quotations. Sites that already rank well in the underlying index get retrieved first. And when independent sources agree on a claim, the engine cites it with more confidence.

Optimizing for AI search citations

To earn AI search citations, make each page easy for a retrieval system to find and easy for a model to quote. Most of the work happens on the page itself, though part of it happens elsewhere on the web.

Write answers a model can lift

Put the direct answer in the first sentence under each heading. A model quotes one passage without the text around it, so give every paragraph a single idea and name things explicitly. If a pronoun points back three paragraphs, the quoted passage won't make sense on its own.

Keep pages crawlable and current

Check that your robots.txt file doesn't block AI crawlers, and keep your key text out of scripts that crawlers can't render. Update figures when they change. A stale number gives the engine a reason to cite a competitor instead.

Earn mentions beyond your own site

Engines check claims against other sources. Reviews and industry press that name your brand give the model independent confirmation. Then test your results: ask the assistants your buyers use the questions you want to own, and note whether they cite you.

Related terms

Once you know what is AI search, read up on GEO next, because it applies everything above. Then ask two assistants about your own category and compare the sources they cite.

The models behind these engines are explained in how LLMs work.