GEO vs SEO: What Changes and What Doesn't

TL;DR

• Generative engine optimisation (GEO) is the practice of increasing how often AI assistants (Gemini, ChatGPT, Claude, Google AI Overviews and Google AI Mode) name, cite and recommend your brand in their answers.
• SEO competes for position on a results page. GEO competes for presence inside a single generated answer.
• The two produce different winners: per an Ahrefs study of 15,000 prompts, only 12% of URLs cited by ChatGPT, Gemini and Copilot appear in Google's top 10 for the same query.
• Most of the underlying work (authority, structured content, earned coverage) drives both. What changes is the target: being cited, not just ranked.
• AEO (answer engine optimisation), GEO and "LLM SEO" (LLM = large language model, the technology behind AI assistants) are near-synonyms for the same discipline. We use GEO.

Generative engine optimisation (GEO), spelled generative engine optimization in US English, is the practice of making your brand and content part of the answers that AI assistants such as Gemini, ChatGPT, Claude, Google AI Overviews and Google AI Mode generate, while SEO is the practice of ranking pages in traditional search results. The difference is not cosmetic: an Ahrefs study of 15,000 prompts found that only 12% of URLs cited by ChatGPT, Gemini and Copilot appear in Google's top 10 for the same query. A brand can rank well and still be absent from the answers buyers actually read. This guide covers what genuinely changes between the two disciplines, what transfers directly, and what to call the whole thing.

What is generative engine optimisation (GEO)?

GEO is defined as the work of increasing how often, and how favourably, generative AI engines mention, cite and recommend your brand when users ask them questions. The term is anchored to the Princeton and Georgia Tech GEO paper presented at ACM KDD in 2024, the study the field treats as its starting point, which tested which content changes increase visibility in AI-generated answers. That Princeton/Georgia Tech GEO paper found that adding statistics boosted AI-answer visibility by 15–40% and expert quotations by 30–40%.

Where SEO asks "does my page rank for this keyword?", GEO asks "when a buyer asks an AI assistant a question in my category, am I part of the answer?" That second question is what AI visibility is: GEO is the practice; AI visibility is the outcome you measure.

What is the difference between GEO and SEO?

The difference between GEO and SEO is the unit of competition: SEO competes for a position on a results page that shows many links, while GEO competes for a mention inside one synthesised answer that may name only a handful of brands. Everything else follows from that.

GEO rewards being cited, not just ranked

The defining shift in GEO is that AI engines reward pages they can cite, and citation behaves differently from ranking. Ahrefs found that around 80% of citations made by large language models (LLMs, the models that generate AI answers) come from pages that do not rank in Google's top 100 at all, and a SEOClarity analysis of 362,000 keywords found that even the number-one organic Google position yields only a 33.07% AI citation rate. On that evidence, ranking first is neither necessary nor sufficient to appear in AI answers.

That is why GEO exists as its own discipline rather than a footnote to SEO. The engines assemble answers from whichever sources they judge most useful for that specific question, which is often a review site, a Reddit thread or a comparison page rather than the official top-ranking result. We cover the mechanics in how AI assistants decide which brands to recommend.

The unit of competition is the answer, not the results page

In GEO the unit of competition is a single generated answer: a handful of brands get named, and every other brand in the category is simply absent. In traditional search, ten or more links share a results page, so visibility is a spectrum: there is no page two of a ChatGPT answer.

AI answers are also probabilistic rather than fixed. SparkToro research found less than a 1-in-100 chance that ChatGPT gives the same list of brands in any two responses to the same query. GEO therefore deals in frequencies (how often you appear across many realistic questions) rather than positions. The wider context is zero-click behaviour: SparkToro also found that in 2026, 68% of Google searches ended without a click. Not every zero-click search is an AI answer, but the direction is the same: more of the buyer's journey resolves on the results surface itself than on a brand's own site.

Whether any of it has transferred for your own brand is a measurable question, not a theoretical one. Run a free AI visibility check to see which buyer questions name you today and which name somebody else, before deciding how much of your SEO work carries over.

What transfers from SEO to GEO?

Most SEO foundations transfer directly to GEO: authority, earned third-party coverage, structured content and crawlability all feed the engines that generate AI answers. GEO is not a restart. What transfers:

• Authority and earned coverage. A Search Engine Land study of 800+ websites across 11 industries found multi-platform brand mentions correlate with AI visibility at r=0.87, and Evertune's analysis of 75,000 brands found brands present on four or more non-affiliated forums are 2.8x more likely to appear in ChatGPT responses. Digital PR and third-party coverage (long-standing SEO work) line up closely with what the engines appear to draw on.
• Structured, extractable content. Clear question-form headings, direct answers, tables and self-contained sections are associated with citation in both search and generative engines. In Kevin Indig's analysis of 1.2 million ChatGPT citations, question marks in headings roughly doubled citation rate (18% vs 8.9%).
• Crawlability and indexation. Grounded AI answers are built on web search retrieval (the engine searches the live web while it answers), so a page that can't be crawled can't be retrieved or cited.
• Ranking itself, for AI Overviews especially. Authoritas and Optimizely studies found 40–76% of Google AI Overview citations also appear in the top 10 organic results. Classic ranking work therefore overlaps most with AI Overviews; the overlap is far looser elsewhere, since an Ahrefs study of 15,000 prompts found only 12% of URLs cited by ChatGPT, Gemini and Copilot appear in Google's top 10 for the same query.

One honest caveat applies to every finding in this guide: nearly all published GEO evidence is correlational. The studies show what AI-cited pages have in common, not what causes a citation. Treat brand mentions, forum presence and question-form headings as directional evidence about what generative engines draw on, not as levers with guaranteed effects.

What doesn't transfer from SEO to GEO?

Three habits from SEO stop working in GEO: rank tracking, keyword-string thinking, and treating your own site as the whole battlefield. Each needs a deliberate replacement:

• The rank-tracking mindset. There is no stable position to track, because answers vary run to run. The meaningful metrics are mention frequency and share of voice (the proportion of all brand mentions across a set of answers that are yours), measured repeatedly over a fixed set of realistic questions.
• Keyword-string thinking. Nobody asks an assistant "best crm software uk cheap". They ask conversational, multi-constraint questions ("what's the best CRM for a 10-person agency that bills hourly?"), and content written for keyword strings misses how those questions are actually answered.
• Treating your own site as the whole battlefield. In Ahrefs' 75,000-brand study, the number of pages on a website showed extremely low correlation with ChatGPT visibility, while YouTube mentions and mention impressions showed the strongest correlation. In GEO, much of the work happens on sources you don't own (review sites, forums, video, press) where the engines go to form their answers.

AEO vs GEO vs SEO: what's the difference in terminology?

AEO (answer engine optimisation), GEO (generative engine optimisation) and LLM SEO are near-synonyms: all three describe optimising to appear in AI-generated answers, and the practical work is the same under any name. The differences are emphasis and audience. AEO frames the target as "answer engines" broadly, LLM SEO is the phrasing SEO-native audiences reach for, and GEO is the term from the academic literature.

We use GEO, for two plain reasons: it is anchored to the Princeton/Georgia Tech research the field treats as its starting point, and it names the actual mechanism, generative engines composing answers, rather than a metaphor. Its one weakness is the acronym collision with location-based "geo marketing", so on first use we always spell out generative engine optimisation. Whichever term you adopt, don't let the naming debate delay the work; the engines don't care what you call it.

How do you measure GEO?

You measure GEO by running a fixed set of realistic buyer questions live through AI engines and recording how often your brand is named, in what position, alongside which competitors, and from which cited sources. A one-off check of your own brand name is not measurement; the signal lives in the non-branded questions, the ones that never mention your brand at all, which is how buyers ask before they know who to shortlist.

This measurement step is what Skavora does. You can run a free AI visibility check that researches your brand, then generates 25 realistic buyer questions from that research, around 80% of them non-branded, because the questions that win new customers are the ones where the buyer doesn't yet know who to ask for. Those questions run live through Gemini with web grounding, meaning the engine searches the live web as it answers rather than replying from training data alone. The free report shows your Visibility Score, your Share of AI Voice (your share of all brand mentions, measured against the brands the engine actually named) and the full breakdown of cited sources, so you know where to earn coverage next. The paid report (£9.99, one-time) runs the same questions across Gemini, ChatGPT, Claude, Google AI Overviews and Google AI Mode. A scan is a snapshot and live answers vary run to run, so re-scan on a cadence; Skavora measures AI visibility, it does not control what the engines say.