Updated 3 September 2026: rewritten around two SearchIntel studies published since the first version, Study 01 (six platforms, 100 UK buying questions, June 2026) and Study 02 (12,264 machine-written searches, September 2026). The original February definition stands; the evidence under it is new.
If you have heard the term, you probably assume Generative Engine Optimisation is SEO with a new name, or a trick for getting ChatGPT to say nice things about you. It is neither. It is the work of getting your brand into the answers that AI systems write, on the questions your buyers ask them, and it is measured against those answers rather than against a rankings page.
Generative Engine Optimisation, GEO, is the practice of making a brand present, accurately described and recommended in AI-generated answers. In 2026 that means six surfaces: ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews and Google AI Mode. The buyer asks a question, the system writes an answer, and the brands named in that answer are the shortlist. GEO is everything you do so that your brand is on it.
The machine does its own searching first
The part most explanations miss is what happens between the question and the answer. In Study 02 we captured 12,264 of the searches ChatGPT, Claude and Gemini wrote for themselves while answering 177 category questions, each run five times, in the UK and Ireland. The engine rarely ran the user's words. It wrote its own searches, usually several, and ran those.
Those self-written searches carried brand names nobody had typed. On 52% of the 89 questions in one market and 66% of the 88 in the other, the engine's own searches named companies before it had read a single page. And being named there matters: across the 438 cases where a competitor's name appeared in the machine's searches, that competitor was mentioned in the answer 87% of the time.
So GEO has a step before content. If the engine does not think of you when it goes looking, your page is competing to be read on a search that was never going to find it. The border case in that study makes the point: one company, same website, same service, appeared in the engine's own searches on 45 of 88 questions at home and once across the border. Asked about it by name in the weaker market, the engine described it accurately. Known, described correctly, not considered. GEO exists to close that gap, and a rankings report cannot see it.
Where the answers get their sources
Once the engine searches, it reads, and what it reads is mostly not brand websites. Muck Rack's May 2026 edition of What Is AI Reading?, built on more than 25 million links cited by ChatGPT, Claude and Gemini, found that earned media accounts for 84% of all AI citations, journalism alone for 27%, and paid or advertorial content for 0.3%. Across all three editions of that study, going back to July 2025, the earned-media share has ranged from 82% to 89%.
Our own scoring points the same way. Across the 75-plus UK brands SearchIntel scored between February and May 2026, the variable that separated the top quartile from the bottom was citation density on the third-party sources the engines trust in each category, not content volume on the brand's own domain. The leading brands in pensions, automotive marketplaces, reviews and flight comparison scored at or near the top by being the category-defining entity in trade press and authority domains. Brands in the same verticals with stronger Google authority and bigger content libraries scored well below them because their off-site footprint was thinner.
The practical difference from SEO is the asset. In SEO your own pages are the asset. In GEO your own pages are the smaller half of the asset, and what the trade press, the review sites, the directories and the forums say about you is the larger half.
Six surfaces, six different shortlists
The second thing the word "optimisation" hides is that there is no single engine to optimise for. In Study 01 we put 100 neutral UK buying questions across 10 industries through all six platforms in grounded mode, 6,119 citations in all, and compared the brands each one recommended. Only 5.3% of the recommended brands were named by all six. The average recommended brand appeared on 2.26 of the six, and 46.1% were named by exactly one. Two platforms answering the same question agreed on under a third of the brands (31.9% mean overlap), and the two flagship chatbots, ChatGPT and Claude, agreed least (22.2%).
Even Google's two surfaces part company once you look at sources rather than brands. On a different measure, which URLs get cited rather than which brands get named, Ahrefs found that AI Mode and AI Overviews cited the same URLs only 13.7% of the time across 540,000 query pairs (Ahrefs, December 2025). So "how do we show up in AI" is six readings, and a brand can be the default answer on one and absent on the next. The work is per platform.
Why it is worth the trouble now
The volume has arrived. Google said at I/O in May 2026 that AI Mode had passed one billion monthly users in its first year (Google, May 2026), on top of the 2 billion-plus monthly users Google reported for AI Overviews in 2025. BrightEdge's tracking through February 2026 put AI Overviews on 48% of tracked queries. ChatGPT passed 900 million weekly users per OpenAI's own disclosure. And the click that SEO was built to win is disappearing underneath all of it: SparkToro's 2026 figures put zero-click US Google searches at 68%, up from 60% in 2024.
None of those numbers is ours, and each has its own scope, so I would not add them together. Taken separately they say the same thing: a large share of the buying questions in your category are now being answered without a results page, and the answer names a shortlist.
GEO and SEO, side by side
The two share some ground. Quality content and authority help both. The mechanics differ enough that you have to run them as separate programmes with separate measurement.
| Aspect | SEO | GEO |
|---|---|---|
| Target | A search engine's ranking algorithm | The answer an AI system writes, and the searches it runs to write it |
| Goal | Rank on the results page | Be a candidate, then be mentioned, then be recommended |
| Main asset | Your own pages and the links to them | What third parties say about you, plus pages the engine can extract from |
| Unit of work | Keyword | Question, per platform |
| Measurement | Search Console, rankings, traffic | Mention rate, recommendation rate, Share of Memory, per platform |
For the longer comparison, including where the two overlap, read GEO vs SEO: What's Different?
GEO, AEO and AI visibility: the same job, three names
You will see all three. Answer Engine Optimisation, AEO, is used interchangeably with GEO by most people, sometimes with a lean toward Google AI Overviews and featured answers. AI visibility, or AI search visibility, is the measurement side: how often you appear. We use GEO for the work and AI visibility for the score. If you want the AEO framing on its own, read What Is AEO?
What GEO work actually is
It comes down to four jobs, in this order.
- Get onto the candidate list. The engine's own searches name companies before it reads anything. Those names come from how consistently your brand is associated with the category across the sources the engine trusts: trade press, review platforms, directories, industry lists, forums. This is the job most GEO plans skip, and in our data it is the one that separates the brands that get recommended from the ones that get read and passed over.
- Be the page the engine can quote. When a search does land on you, the page has to answer the question in the first hundred words, state the facts an engine checks (what you do, for whom, where, since when, at what price where that is public), and carry structured data that says the same thing. FAQ and Organization schema are hours of work, not weeks, and they are what the engine extracts.
- Say the same thing everywhere. Entity consistency is a real signal. If your positioning is described three different ways across your site, your directory listings and your press coverage, the engine has three weak associations instead of one strong one.
- Measure per platform, and keep measuring. Run a fixed set of the questions your buyers ask across all six surfaces, on a schedule, and record who is named and who is recommended. Not once. The answers move.
I want to be careful about what that list does not say. It does not say publish more. Several of the brands in our scoring with the biggest content libraries scored below smaller rivals with better third-party footprints. Content matters when a search reaches it; it does not by itself get you into the search.
How to know if it is working
You cannot read GEO off Google Search Console alone. Referrals from AI answers are thin and inconsistently labelled, and the recommendation you missed sends nothing at all. Search Console does now show you some of the searches the engines write, which is useful for seeing how the machine phrases your category, but it will not tell you whether you were the answer.
The measure is Share of Memory: the percentage of relevant AI questions in which your brand appears, read per platform. A brand at 40% is in four of every ten relevant answers; a brand at 5% is in one in twenty. Below it sit two more readings, the recommendation rate (named as a choice, not just mentioned) and the citation rate (your pages used as a source). Six platforms, three readings each, on the same question set, over time, and nothing else on the scoreboard. SearchIntel runs it as a service; the methodology is public, and the free check gives you a first reading on five of the six surfaces.
One limit, stated plainly. Our two studies are UK and Ireland, one on 100 questions and one on 177, captured on the model versions current in June and July 2026. The percentages above are those datasets, not a law. The direction has held on every category we have scored since. So I am comfortable building the definition on it, and we keep re-running the questions.
Questions people ask about GEO
What does GEO stand for?
Generative Engine Optimisation: the work of getting a brand present, accurately described and recommended in the answers AI systems generate, on ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews and Google AI Mode.
Is GEO the same as SEO?
No. SEO targets a ranking algorithm and your own pages are the main asset. GEO targets the answer an AI writes and the searches it runs to write it, and what third parties say about you is the larger part of the asset. In Muck Rack's May 2026 data, 84% of AI citations were earned media, not brand sites.
Is GEO the same as AEO?
In practice yes. Answer Engine Optimisation is the same job under a different name, sometimes used with a lean toward Google AI Overviews. AI visibility is the measurement of either.
Do I need a different approach for each AI platform?
Yes. In our June 2026 study only 5.3% of recommended brands were named by all six platforms and 46.1% were named by just one, so a single check on one platform shows you a different picture, not a smaller one.
How do I measure GEO?
Run a fixed set of buyer questions across all six platforms on a schedule and record whether your brand is mentioned, recommended and cited. Report it per platform as Share of Memory. Search Console alone cannot show you the recommendations you missed.
What is the first thing to do?
Find out whether the engines think of you at all. If your brand is not in the searches the engine writes for your category questions, no amount of on-site content fixes that, and the work starts with third-party citations and entity consistency. If it is, the work starts on the pages the engine lands on.