---
title: "What Is Generative Engine Optimisation? | Gudu"
description: "Generative engine optimisation, defined plainly: what GEO is, what it isn’t, and what the work looks like for an Australian business in 2026."
canonical: https://gudu.com.au/what-is-generative-engine-optimisation/
---

# What generative engine optimisation actually is

By Jordan Parrello · August 27, 2026

Generative engine optimisation got a sales pitch before it got a definition. I’ve read agency pages that use the term nine times without once saying what it means, which is a poor look for a discipline whose entire job is answering a question clearly.

So this is the definition, written to be lifted. If you want the practical mechanics rather than the meaning, we published those separately in [how to get your brand cited in ChatGPT and AI Overviews](https://gudu.com.au/how-to-get-cited-in-ai-answers/).

## The definition, in one paragraph

Generative engine optimisation, usually shortened to GEO, is the practice of making a brand and its content easy for AI systems to find, understand and cite, so that the brand gets named inside the answers those systems write. Search engine optimisation earns you a ranking and a click. GEO earns you a mention inside the answer, where there is no list of ten links to be fifth on.

That’s the whole thing. Everything below is elaboration.

## What a generative engine is

A generative engine is any system that responds to a question by writing an answer instead of returning a list of links. ChatGPT, Gemini, Claude, Copilot and Perplexity are the obvious ones. Google’s AI Overviews are the one that matters most to most Australian businesses, because they sit on top of the search results people were already going to look at.

The distinguishing feature isn’t the AI. Google has used machine learning in ranking for years. It’s the output. A ranked list gives you ten chances to be chosen. An answer gives you one, and it usually names two or three brands.

## Why the term needed to exist

Ranking fifth on page one used to be worth money. In a generated answer there is no fifth. You are cited or you aren’t, and if you aren’t, the customer often never learns you exist, because the question got resolved before anyone scrolled.

That changes what optimisation is aiming at. Not a position, a mention. New target, new name, and for once the new name is doing real work rather than repackaging the old one.

It also changes who can win. Whether you get cited depends heavily on whether a machine can confirm who you are and whether your page answers the question cleanly, and neither of those is a function of how old your domain is. That’s the one genuinely encouraging thing in this for smaller Australian businesses.

## Four names for the same job

You’ll see this sold as AI SEO, LLM SEO, answer engine optimisation and AI search optimisation. The work underneath is the same; the only reason for four names is that four groups of people each coined one. Ahrefs’ Australian data has “ai seo agency” at roughly 900 searches a month, while every generative engine optimisation variant comes back with no measurable volume at all (Ahrefs, August 2026). The plain-English name is winning the search traffic. The technical one is winning the industry conversation.

There’s a practical consequence. Don’t buy it twice. If an agency quotes SEO and then quotes GEO as a separate engagement, ask which tasks appear on only one of the two lists. The honest answer is a short list.

## What GEO is not

It isn’t a replacement for SEO. When you ask an assistant something specific, it runs a search and reads a handful of pages before it writes anything. If you’re not in that handful, nothing else you’ve done matters, because you can’t be quoted from a page nobody opened. Our explainer on [SEO versus GEO](https://gudu.com.au/seo-vs-geo-whats-the-difference/) works through that dependency properly.

It isn’t a placement you can buy. No auction, no submission form, no rate card. Anyone selling guaranteed inclusion in ChatGPT is selling something they can’t deliver.

It isn’t schema markup on its own. Structured data helps a machine understand what’s already on the page. It won’t make a thin page worth quoting, and no amount of it will get a vague services page cited ahead of a competitor who published the actual answer.

And it isn’t measurable in search volume. None of the assistants publish query counts. If someone quotes you a monthly volume for an AI search term, they made it up.

## What the work consists of

Four things, none of them exotic.

The first is entity clarity. One company name spelled one way everywhere you appear, one plain description of what you sell and where, consistent across your site, LinkedIn, your Google Business Profile and any directory that lists you. Where those disagree, a model can’t confirm you’re who your page says you are, so it cites someone it can confirm instead.

The second is structure a machine can quote. Ask the question in the subheading, answer it in the next forty to sixty words in complete sentences that don’t lean on the sentence before them, then elaborate underneath for as long as you like. Real tables with real header cells, rather than a comparison written as four flowing paragraphs.

The third is facts only you hold. Assistants cite whoever sits closest to a number. Publish your own results, your own pricing logic, what you see across your client base, dated and with the method attached, and you become the source instead of a site repeating one.

The fourth is mentions elsewhere. Models build their sense of who’s credible from the wider web: trade press, established directories, review sites and the reference sites those feed. That’s ordinary digital PR judged against a different outcome, and it’s the slowest part by a distance.

## How you tell whether it is working

Pick twenty questions your customers actually ask, run them through the assistants once a month, and record who gets named. Your score is share of answers out of twenty. It moves slowly and it wobbles between runs, so treat any single result as a sample rather than a position.

Two harder numbers sit alongside it. Google reports AI Overview features, which is a real count: AGL’s search programme with us produced 14.5k of them, alongside a 58% lift in average search position from the same work. The [AGL case study](https://gudu.com.au/agl/) has the rest of it. Separately, GA4 has begun logging an AI Assistant traffic channel, which is where we first saw assistants sending people to Pace’s new pages in June, written up in the [Pace case study](https://gudu.com.au/pace/).

Neither is a complete picture. Together they beat guessing.

## Does an Australian business need this yet

Depends what you sell.

If your customers do any research before they buy, and especially if they compare suppliers or ask what to look for, then yes, because that’s precisely the shape of question people now hand to an assistant instead of a search box. If you sell on price and proximity, the way a takeaway or a car wash does, this matters far less than your Google Business Profile does.

The Australian wrinkle is which surface to care about. AI Overviews reach people who never chose to use an AI product; they just searched, the way they always have. For most businesses here that’s the bigger audience and the easier one to influence, because the work that gets you into an Overview is mostly the search work you should be doing anyway.

## Where to start

Open ChatGPT and type the question your best customer would type. Not your brand name. The question. Whoever gets named in the answer is your competitive set now, and it’s frequently not the list in your board deck.

Do that twenty times and you’ll know the size of your problem before lunch. What to do about it is in [how to get your brand cited in ChatGPT and AI Overviews](https://gudu.com.au/how-to-get-cited-in-ai-answers/), and the version we run for clients is [generative engine optimisation](https://gudu.com.au/services/technology/geo/).