GEO vs SEO: what actually changes when buyers ask AI instead of Google
Search used to end with a page of ten blue links. Increasingly it ends with a paragraph. A buyer asks ChatGPT or Perplexity for the best option in their market, and the engine hands back a short recommendation naming two or three brands. If you are not one of them, you were never in the running, and there is no second page to climb to.
The one-sentence difference
SEO gets you ranked. GEO gets you named. Search Engine Optimization is about winning a position on a results page so a person can choose to click you. Generative Engine Optimization is about being cited and mentioned inside the answer the AI writes, so the buyer never has to choose from a list at all. One competes for a slot. The other competes to be the recommendation.
Where they overlap, and where they part ways
The good news is that GEO is not a rebuild. Generative engines lean heavily on content that is already structured well for search: clean HTML, proper headings, fast server-rendered pages, accurate schema. If your SEO foundations are weak, your GEO will be too. That shared base is why the sensible posture is SEO plus GEO rather than a migration from one to the other.
They part ways on what actually wins. Below the shared foundation, the two disciplines optimise for different behaviours.
| Dimension | Classic SEO | GEO / AEO |
|---|---|---|
| Goal | Rank on the results page | Be cited and named in the answer |
| Unit of visibility | A blue link | A brand mention plus a source citation |
| How the query is processed | One keyword, one results page | The prompt is fanned out into many sub-questions |
| Strongest off-site signal | Backlinks | Branded mentions on credible pages |
| Surfaces to win | Mainly Google | Many engines, roughly 86% of sources unique to each |
| What the visitor does | Clicks through to compare | Often arrives already convinced, or never clicks |
Five things GEO asks of your content that SEO did not
Answer first. Generative engines chunk a page and keep the parts that directly resolve a question. State the takeaway in the first one or two sentences of a section, then elaborate. Burying the point three paragraphs down means it gets skipped.
Write for the fan-out, not the keyword. An engine does not treat your prompt as a single query. It expands it into dozens of narrower sub-questions and assembles the answer from whatever content resolves them. Depth on specific, buyer-real questions beats broad category pages stuffed with terms.
Earn branded mentions, not just links. Every time your brand appears on a credible, well-linked page in a relevant context, the model sees another example associating you with the topic. In generative visibility, that pattern of mentions correlates more strongly than backlink counts.
Diversify by engine. Because most cited domains are unique to a single engine, the sources that get you into ChatGPT are usually not the ones that get you into Google AI Overviews or Perplexity. Each engine has its own preferred neighbourhood, and you have to show up in each.
Make the machine-readable layer explicit. Correct schema, an llms.txt file, and a robots.txt that does not accidentally block AI crawlers are the difference between being readable and being invisible. You cannot be cited from a page an engine cannot retrieve.
The European wrinkle worth knowing
Most GEO research is US-sourced, which hides a fact that matters a lot for French and wider EU brands. As of mid-2026, France has not been hit by Google AI Overviews the way Spain and Italy already have, largely because of the ongoing dispute over neighbouring rights. That is a dated, closing window: the change is coming, and the brands that build their answer-engine presence before it lands will be the ones the AI already knows how to recommend.
The demand is real. Médiamétrie measured that by September 2025 close to four in ten people in France had used a conversational AI agent, with ChatGPT far in front. But be honest about the mechanism: click-through from the body of an AI answer is low, often under one percent. GEO earns its keep as brand visibility and buyer-journey influence, being in the room when the AI makes a recommendation, not as a firehose of referral clicks.
The practical test. Open ChatGPT, Perplexity and Google AI in a clean incognito window and ask the question your best buyer would ask: the best option in your category, in your city, for your use case. Note whether you appear, what the engine says about you, and which sources it cites. That five-minute check is the whole GEO problem in miniature.
So is SEO dead?
No, and anyone selling that line is usually selling a replacement product. Traditional search still carries most buyer research, and it feeds the generative layer directly. The right move is to orchestrate both: keep the SEO foundations strong, then add the GEO layer that gets you cited and named where buyers increasingly make their shortlist. The work is not measuring how invisible you are. Plenty of tools already do that well. The work is shipping the fixes.
Frequently asked questions
If 86% of cited sources are unique to a single engine, where should we start?
Start with the engine your buyers actually use, not the one with the best press. Sample the same twenty buyer-intent prompts across ChatGPT, Perplexity, Claude and Google AI, and count where competitors get named and you do not. That tells you which engine's citation neighbourhood is costing you deals right now. Work that one until you are consistently in the answer, then move to the next. Trying to cover all of them at once spreads the source-building work so thin it moves nothing.
Why has France not seen Google AI Overviews yet, and when does that window close?
Largely because of the ongoing dispute over neighbouring rights, which has held back the rollout in France while Spain and Italy already have it. Nobody outside Google knows the exact date it lands, so treat it as a dated advantage rather than a permanent one. The practical consequence is that French brands can build their answer-engine presence before the surface arrives, and models tend to keep recommending whoever they already associate with a category. Waiting until Overviews appear means building that association against competitors who started earlier.
If click-through from AI answers is under 1%, how does GEO pay for itself?
Not through referral volume, and any pitch built on traffic numbers is selling the wrong thing. It pays through being in the consideration set: when a buyer asks an engine for the best option in your category and it names two or three brands, you are either one of them or you were never in the running. The visits that do arrive convert unusually well because the buyer comes pre-qualified by the recommendation. The honest way to size it is to work out how many additional customers the work has to win to cover its cost, then judge whether that number looks reachable for your category.
Which of our existing SEO foundations already feed GEO?
More than most teams expect. Clean HTML, a sensible heading structure, fast server-rendered pages and accurate schema all carry straight over, because generative engines lean heavily on content that is already well structured for search. That shared base is why the sensible posture is SEO plus GEO rather than a migration. What does not carry over is the keyword-and-backlink layer: GEO wants answer-first passages, depth on narrow buyer-real questions, and branded mentions on credible pages rather than link volume. If your SEO foundations are weak, fix those first, GEO built on a site an engine cannot retrieve is wasted effort.
See how you show up today.
The free Snapshot checks how your brand appears across ChatGPT, Perplexity, Claude and Google AI in your market, then hands you a ranked list of fixes. No card, no commitment.