What is Generative Engine Optimisation (GEO)?

By Jack Gallagher-Bohn, Founder · Published 29 July 2026 · Updated 30 July 2026

Ask a question in ChatGPT or Google and, increasingly, you don't get ten blue links — you get one written answer, with a handful of sources behind it. GEO is the discipline of becoming one of those sources. Where traditional SEO competes for a ranked position on a results page, GEO competes for the citation inside the answer itself.

The term is young but the shift is measurable. Searches for "generative engine optimization" grew 997% over 18 months according to Ahrefs' own keyword database, and research by Search Engine Land and Third Door Media found GEO has the highest recognition of any term for the discipline — 84% of practitioners know it, and 42% already use it. Traffic referred by AI search grew 527% year on year, according to Semrush.

GEO, AEO, AI SEO, LLM SEO: the acronym zoo

The industry hasn't settled on one name, which makes the space feel more complicated than it is. Every term below describes the same underlying work:

So, what is AI SEO? It's the same thing as GEO in plain clothes: the umbrella phrase people type when they don't know the acronym. If you remember one distinction, make it this one — GEO is the strategy (entities, authority, knowledge-graph signals) and AEO is the tactic (writing the specific, self-contained passage an engine can lift into a specific answer). Everything else is branding.

How AI engines choose what to cite

People often ask how to rank in ChatGPT. Strictly speaking, you don't — there's no ranked list to climb. You get retrieved, and then you get quoted, and understanding that two-step is most of the game. AI engines don't browse the web the way people do. Most of them answer in two steps: retrieve, then write. The engine runs a search against an index (Google's, Bing's, or its own crawl), pulls a shortlist of candidate pages, and then writes an answer grounded in what those pages say — citing some of them. That means two separate filters decide whether you appear: you have to be retrievable (ranked well enough to make the shortlist — which is classic SEO), and you have to be quotable (written and structured so the model can lift a claim cleanly and attribute it to you).

Quotability is where GEO earns its keep. The peer-reviewed research that named the field — "GEO: Generative Engine Optimization", from Princeton and Georgia Tech researchers (KDD 2024) — tested nine optimisation methods across thousands of queries and found the right ones lift a site's visibility in AI answers by up to 40%. The tactics that worked weren't exotic: adding quotable statements, citing sources, and including statistics outperformed keyword-stuffing, which sometimes made visibility worse. Engines reward pages that read like evidence, not like advertising.

• Retrievability — solid rankings and crawlability get you into the candidate set.
• Parseability — semantic HTML and structured data let machines read your meaning.
• Extractability — self-contained, answer-first passages are what models quote.
• Entity clarity — engines cite businesses they can identify and disambiguate.
• Evidence — sourced claims, statistics, and quotations outperform sales copy.

One practical wrinkle: the engines don't share a single source of truth. ChatGPT's browsing and Microsoft Copilot lean on Bing's index; Gemini and AI Overviews draw on Google's; Perplexity runs its own crawler on top of web search. That's why GEO work targets the common denominators — clean crawlability, consistent entities, quotable structure — rather than chasing any one engine's quirks. Optimise the substrate and every engine that reads it benefits.

GEO vs SEO: complement, not replacement

The honest answer to "GEO vs SEO" is that it's the wrong fight. SEO earns rankings; GEO earns citations — and the citation engines pick their sources from the ranked, crawlable web. Google's public position is blunt: optimising for AI features is still SEO. A site with weak foundations doesn't need a GEO specialist, it needs its crawl, speed, and content fixed — after which GEO is a surprisingly short step, because entity work, structured data, and answer-first writing sit on top of the same infrastructure.

A useful way to hold the relationship in your head: everything that made a site good at SEO — crawlable architecture, fast pages, real authority, content that answers the query — transfers directly to GEO. What GEO adds on top is a short list: passages engineered to be extractable, entities defined precisely enough for a model to disambiguate you from every other business with a similar name, and a measurement habit for a surface that has no official analytics. It's an extension, in the same way local SEO extended SEO a decade ago — a new distribution channel on shared foundations.

Is SEO dead now that AI answers questions?

No — and the volume data says so. Plain "SEO" still draws roughly 250,000 monthly searches in the US alone (Semrush data, via Backlinko), dwarfing every new acronym. What is true is that the click economics are shifting: Google's AI Overviews now reach around 2 billion users a month, and when an AI Overview appears, click-through on the top organic result drops by roughly 35–58% depending on the study (Ahrefs; Search Engine Land). Search isn't dying; the answer layer is absorbing the clicks. The rational response isn't abandoning SEO — it's making sure that when the answer layer summarises your market, you're the business it names.

What AI Overviews mean for your traffic

AI Overviews are the clearest local example of the shift, because they sit inside the Google results Australians already use. When one appears above your #1 ranking, a share of your clicks evaporates — but the Overview itself cites sources, links them, and sends higher-intent visitors to the pages it trusts. The strategic takeaway: a ranking you hold today is worth defending with the structure and evidence that gets you cited tomorrow, on the same page, above your own listing.

What GEO work actually involves

Practised properly, GEO is four layers of unglamorous engineering. First, entity work: defining your business, people, and services as machine-readable entities so engines know exactly who you are. Second, structured data: validated schema markup that turns your pages from prose into parseable facts. Third, content engineering: rewriting key pages into answer-first, self-contained passages that carry evidence — the format the KDD research found engines reward. Fourth, measurement, covered below. Some practitioners add an llms.txt file — an emerging convention that describes your site to AI crawlers. It costs little and we ship one ourselves, but treat it as a courtesy signal, not a ranking lever: major engines don't commit to reading it.

The entity layer deserves a concrete example, because it's the least visible. To a language model, "who is the best plumber in Norwood" is an entity-resolution problem: it has to connect a name to a place, a service, and evidence of standing. You help it by being ruthlessly consistent — one exact business name everywhere, one address format, Organization and Person schema that match your visible copy, an About page with real humans on it, and profiles that corroborate each other. Boring, checkable work. It's also exactly what most competitors skip.

How do you measure whether it's working?

With discipline, because there's no Search Console for ChatGPT. The workable method is a tracked prompt set: a fixed list of questions your customers actually ask, run against each engine on a schedule, from a clean session, with every response logged. Each run records two different things — whether you're mentioned (named in the answer) and whether you're cited (linked as a source) — plus which competitors appear beside you. Run it monthly without changing the prompts and you get a citation-share trend you can actually act on. Anyone selling GEO without a measurement method like this is selling weather.

Prompt design matters more than volume. A good set mixes the question types buyers actually use: "best X in Adelaide" recommendations, direct comparisons against competitors, problem-first questions where your service is the answer, and branded checks on your own name. Keep the wording frozen — edit a prompt and you've broken the series — and log the engine version alongside each run, because model updates can move results overnight through no action of yours. The discipline is tedious. It's also the only thing separating a measured GEO programme from an invoice with a story attached.

Do you actually need GEO yet?

Honest sizing: it depends on how your customers buy. If your buyers research before they spend — professional services, B2B, considered purchases, anything where people ask "who's the best X in Adelaide" — the answer layer is already shaping their shortlist, and early movers are being cited into it while competitors ignore it. If you run a pure walk-in business with no research step, foundational SEO and a fast site still matter more. And if the budget only stretches to one thing: fix your SEO foundations first. Every GEO tactic is cheaper and more effective on a site that already ranks.