AI Search Optimisation: How to Get Cited by ChatGPT and AI Overviews

AI search optimisation is the work of getting your business named and cited in AI-generated answers from ChatGPT, Google AI Overviews, Perplexity and Gemini. You earn citations with clear answer-first content, clean structured data, consistent entity and brand naming, real named expertise, mentions on other trusted sites, and an llms.txt file. It is also called generative engine optimisation, or GEO.

People used to search, scan ten blue links, and click. More of them now ask an AI and read the answer it writes back, with a handful of sources cited underneath. If your business is not in that answer, you are invisible to that buyer, even when your normal Google rankings are fine. This is what AI search optimisation fixes. Here is how it works, where it overlaps with ordinary SEO, where it differs, and what to do first.

What AI search optimisation is

AI search optimisation is the practice of making your content easy for AI systems to read, trust and quote. It goes by a few names: generative engine optimisation (GEO) is the most common, and answer engine optimisation (AEO) is the same idea aimed at tools that answer questions. They describe one goal: when someone asks an AI assistant about a problem you solve, your business is the source it cites.

It matters now because the front page of the internet is changing shape. Google AI Overviews sit above the normal results on a large and growing share of searches. ChatGPT, Perplexity and Gemini answer outright, cite a few sources, and many people stop right there. For commercial and local queries, the buyer often reads the AI answer and acts on it without clicking.

How AI systems choose what to cite

AI search engines do not rank pages the way classic Google does. They read a question, gather candidate sources, and assemble an answer from the ones they trust and can quote cleanly. A few signals decide whether your content makes the cut.

Clear, direct-answer content

An AI extracts the answer, so the answer has to be extractable. Put it plainly near the top of the page, in a sentence or two a machine can lift without guesswork. Use real question-shaped headings and answer each one directly underneath. Pages that bury the point under three paragraphs of warm-up get skipped. Answer first, explain second, every time.

Clean structured data

Structured data, also called schema markup, is code that tells a machine what your page is: an article, a product, a local business, an FAQ. AI systems and the search indexes feeding them lean on it to read a page without parsing every word. Mark up your business details, your articles with their author, and your FAQs. It is one of the highest-return jobs in AI search optimisation, because it turns prose a machine has to interpret into facts it can simply read.

Consistent entity and brand naming

AI models reason about the world as entities: people, companies, products, places. To cite your business confidently, the model needs to see the same business described everywhere it looks. So name yourself the same way every time, across your site, your Google Business Profile, your directory listings and your social profiles. Same name, same address, same description. Inconsistent naming splits your identity in the model’s view and weakens every signal you have.

Real named expertise and E-E-A-T

Google calls it E-E-A-T: experience, expertise, authoritativeness and trust. AI systems lean on the same idea when they decide who is worth quoting. Content written by a named person with genuine knowledge, a real bio and a track record carries more weight than anonymous filler. An article written by someone who actually does the work, and is named as doing it, is far likelier to be cited than generic text with no author at all.

Being a source other trusted sites reference

AI models build their picture of you from the whole web, not just your own site. When other reputable sites mention your business, cite your data, or link to your work, the model treats you as more authoritative and is likelier to name you. This is the AI-era version of off-page authority. You earn it the slow, honest way: useful content, real mentions, and being the source people quote, not buying links, which is as risky here as it has always been.

An llms.txt file

An llms.txt is a plain text file you place at the root of your site, like robots.txt, that gives AI systems a clean map of your most important pages and what they cover. It is an emerging convention, not yet a guarantee that every model reads it, but it hands AI crawlers a tidy summary instead of leaving them to work it out from scratch. We add one as standard, because the downside is nil and the upside is real as adoption grows.

How it overlaps with traditional SEO, and where it differs

Most of AI search optimisation is good SEO done with intent. The overlap is large, which is the reassuring part: clean technical foundations, useful content, structured data, named authors and real authority help you in classic Google search and AI answers at once. If someone sells you “GEO” as a brand-new discipline with nothing in common with search engine optimisation, be sceptical. The foundations are shared.

The differences are narrower than the hype suggests. Three stand out:

• The answer can replace the click. Classic SEO wins the click. AI search often answers without one, so being the cited source matters even when no visit follows. Your brand being named is a goal in its own right.
• Extractability beats positioning. Ranking first helps, but an AI assembles its answer from whichever sources it can quote most cleanly. A clear page at position four can get cited over a rambling one at position one.
• Your whole web presence is the input. A normal search ranks one page. An AI builds its view of you from your site, your profiles and your mentions. The unit of optimisation is your entire entity, not a single URL.

So AI search optimisation is not a replacement for SEO, nor a trick bolted on afterwards. It is the same craft, with answer-first writing, schema and entity consistency treated as first-class work.

Aspect	Traditional SEO	AI search optimisation
Goal	Win the click to your page	Be the source the AI answer cites
What wins	Ranking position	Clear, extractable answers
Unit optimised	A single page	Your whole entity: site, profiles and mentions
Outcome	A visitor lands on your site	Your brand named, with or without a click
Shared foundation	Clean tech, useful content, schema, named authors	The same foundations, treated as first-class

What a business should do first

Start with the foundations. They pay off in both AI answers and ordinary rankings at once. In order:

• Make your core pages answer-first. Put a clear, direct answer to the obvious question near the top of your home page and main service pages. This is the single highest-return change, and you can start today.
• Add structured data. Mark up your business, your articles and their authors, and your FAQs so machines read your pages as facts, not guesswork.
• Fix your entity consistency. Make your business name, address and description identical across your site, Google Business Profile and every listing. This doubles as local SEO for businesses that serve a place.
• Put real authors on your content. A named expert with a genuine bio earns trust from Google and AI systems alike.
• Add an llms.txt. Cheap, low-risk, and increasingly useful as AI crawlers adopt it.

That sequence costs little beyond effort and lifts you in normal search at the same time. It is the same answer-first approach we cover for smaller operators in our guide to SEO for small business, applied with AI citations in mind.

How Caffeinate approaches AI search optimisation

We build for this on every page, not as an add-on. New pages ship answer-first, with schema and clean entity naming as standard. We also run AI-first ourselves, which is the honest reason we take it seriously. Our own AI agents work on the Google Ads API overnight, auditing accounts and drafting optimisations, and a senior human reviews and ships every change. We build our own software too, including Odin Dealer, a dealership CRM, and ConversAI, our AI live chat. We understand how AI systems read and cite content from the inside, not from a blog post.

Where AI search is the whole game, we run dedicated AI search optimisation as a focused program. Where it is one part of a wider plan, we fold it into our broader AI solutions work. Either way the principle holds: build for clarity and trust, and you win in Google and AI answers together.

Frequently asked questions

What is the difference between AI search optimisation, GEO and AEO?

They describe the same goal with different labels. Generative engine optimisation (GEO) is the most common name and focuses on generative AI tools like ChatGPT and Google AI Overviews. Answer engine optimisation (AEO) emphasises directly answering questions. In practice they overlap almost entirely, so do not get hung up on which label an agency uses.

How do I get cited by ChatGPT?

Make your content easy to read, trust and quote. Answer the question plainly near the top of the page, add structured data, name your business consistently everywhere, put real authors on your work, and earn genuine mentions from other reputable sites. There is no paid placement and no guaranteed trick. You become a source AI trusts by being clear, expert and consistent.

Does AI search optimisation replace SEO?

No. It extends it. Most of the work, from clean technical foundations to structured data and named authors, helps you in classic Google search and AI answers at once. The differences are narrow: AI can answer without a click, it rewards extractable clarity over raw position, and it judges your whole web presence rather than one page.

Is llms.txt worth adding?

Yes, on a cost-versus-benefit basis. It is a small plain text file at the root of your site that gives AI crawlers a clean map of your key pages. Not every model is confirmed to read it yet, but it carries no downside and becomes more useful as adoption grows. We add one as standard.

How long until AI search optimisation shows results?

It varies, and anyone who promises a fixed timeline is guessing. Structured data and answer-first changes can be picked up reasonably quickly once AI systems recrawl your pages. The entity consistency and authority side compounds over months, like all trust signals. Expect steady progress rather than an overnight jump, and treat being cited at all as the win.

Talk to a Perth agency that builds for this

Caffeinate is a Perth-based, AI-first agency working with businesses across Australia, from car dealerships and trades to professional services and retailers. We build every page answer-first and know how AI systems read and cite content from the inside. If you want your business named in the answers buyers now read before they click, take a look at our AI search optimisation service or get in touch for an honest read on where to start.