AI search optimisation
In short
AI search optimisation is answer engine optimisation and generative engine optimisation under a plainer name — one discipline, three labels, not three techniques. What the phrase adds is an emphasis on coverage: ChatGPT, Perplexity, Google's AI Overviews, Gemini and Claude retrieve and cite differently enough that presence in one is no evidence of presence in another, so each is checked and reported separately rather than averaged into a single score. This page canonicalises to the service page, because it describes the same offering rather than a second one.
This page carries a rel=canonical to getting found when buyers ask AI. It exists because "AI search optimisation" is what a lot of people actually type, and it should lead somewhere that answers the question — but it describes the same single service rather than a second one, and it says so rather than pretending otherwise.
Are AEO, GEO and AI search optimisation different things?
No. They are three names for one discipline: making a company's information retrievable and citable by systems that answer a question in prose instead of returning ten links. Answer engine optimisation (AEO) is the term buyers and agencies use. Generative engine optimisation (GEO) is the term that came out of the academic literature. AI search optimisation — or AI search optimization, if you spell it the American way — is the same idea described without an acronym.
The terminology diverged because the practice and the research arrived at it separately and at roughly the same time, not because there are three techniques. If a proposal quotes them as separate line items, that is a pricing decision, not a technical one.
So why does the phrase "AI search" exist at all?
Because it carries an emphasis the acronyms do not: coverage. "AI search" is the reminder that this is plural. ChatGPT, Perplexity, Google's AI Overviews, Gemini and Claude are separate systems with separate retrieval behaviour, and treating them as one channel is how a report ends up saying nothing.
Why does each engine have to be checked separately?
Because appearing in one is not evidence of appearing in another. They differ in where they retrieve from, how many sources they pull per answer, how densely they cite, and how much they lean on classic search rankings underneath. A blended "AI visibility score" averages those differences away and hides the only thing worth acting on — which engine is missing you, and what it is reading instead.
One published measure of how far apart the layers now sit: Ahrefs found in March 2026 that 38% of pages cited in Google's AI Overviews also ranked in the top ten for the same query, down from 76% in July 2025. That is one engine's relationship with one ranking system, over eight months. It is not a number you should assume holds for the others.
Do these systems read my site the same way Google does?
Mostly not, and the difference is mechanical rather than editorial. Vercel and MERJ tracked over 500 million GPTBot requests in December 2024 and found no evidence of JavaScript ever being executed — GPTBot requested JavaScript files 11.5% of the time and ClaudeBot 23.8%, and neither ran them. Gemini and Applebot are the exceptions, because they reuse rendering infrastructure that already exists.
The practical consequence: if your pages are assembled in the visitor's browser rather than on the server, most of these crawlers receive a near-empty document. No amount of writing fixes that. It is the first thing worth testing, and testing it takes minutes.
Where should I go from here?
If you want the service, it is here, under the name a buyer would use rather than an acronym. If you want the terminology explained properly, including where GEO came from, read what answer engine optimisation is. If you want to know whether any of this applies to your company specifically, the answer is an empirical one:
Frequently asked questions
Which AI engines should I be optimising for?
The ones your buyers use, which usually means checking ChatGPT, Perplexity, Google AI Overviews, Gemini and Claude separately. They differ in how they retrieve and how densely they cite, so being present in one is not evidence of being present in another. Reporting a single blended score across engines hides the pattern that matters.
Do AI crawlers run JavaScript?
Mostly no. Vercel and MERJ reported in December 2024 that none of the major AI crawlers execute JavaScript: GPTBot requested JavaScript files 11.5% of the time and ClaudeBot 23.8%, and neither ran them. Gemini and Applebot are the exceptions because they reuse existing rendering infrastructure. If your content only appears after JavaScript runs, most of these systems never see it.
My site is a React or Vue single-page application. Is that a problem?
It depends entirely on whether it is server-rendered or statically generated. A client-rendered application serves an almost empty HTML document to a crawler that cannot run scripts. Frameworks like Next.js, Nuxt, SvelteKit and Astro all have server-rendered or static modes that solve this without a rewrite, so the first step is establishing which mode you are actually in.
How do I check this myself?
Request one of your pages with a crawler user-agent and no JavaScript execution, then search the returned HTML for a phrase you know is on the page. If the phrase is missing, the content does not exist as far as most AI crawlers are concerned. The free check includes this test and reports the raw result either way.
Find out what the engines currently say about you
Send me your company name and website. I run a set of buyer questions across ChatGPT, Perplexity, Gemini, Claude and Google's AI Overviews, and send back a recorded walkthrough of what came out: where you appeared, where you did not, who was named instead, and the two or three structural reasons why. No charge, no obligation, and you keep the findings whether or not you decide to hire me.
I run these myself, so there is a queue. Expect a few working days rather than an instant report.