GEO vs AEO vs SEO: what the terms mean and where they overlap
Three acronyms describe one shift in search. Here is what each term actually refers to, where the work genuinely differs and where vendors are selling you the same thing twice.
The vocabulary in this category is a mess and some of that is deliberate. New acronyms make familiar work sound like a new product. It is worth being precise about what each term means before you buy anything described with one.
The short version
| Term | Stands for | The question it answers |
|---|---|---|
| SEO | Search engine optimization | Will my page rank in a list of results? |
| AEO | Answer engine optimization | Will my content be the direct answer to a question? |
| GEO | Generative engine optimization | Will my brand be quoted inside an AI-generated response? |
| LLMO | Large language model optimization | A newer label, broadly interchangeable with GEO. |
The honest summary: these are not four disciplines. They are one discipline viewed from four angles, with perhaps 70% overlap in the underlying work.
Search engine optimization
The original and still the largest. Make pages that are crawlable, relevant and authoritative enough to rank in an ordered list of results. Technical health, content quality, internal linking and earned links from other sites.
This has not gone away and will not go away soon. For most businesses it remains the single largest source of commercial organic traffic.
Answer engine optimization
AEO predates the current AI wave. It grew up around featured snippets, “People also ask” and voice assistants, contexts where a search engine extracts one answer rather than presenting a list.
The practical work: answer the question directly and early, use a heading that matches how the question is actually phrased, keep the answer compact enough to be extracted whole and structure comparisons as tables and procedures as numbered steps.
If you optimised for featured snippets in 2019, you have done AEO.
Generative engine optimization
GEO is the newest term and refers to being cited inside a response that a model composes rather than extracts. The difference matters more than it sounds.
A featured snippet lifts a passage verbatim from one page. A generated answer synthesises several sources and writes something new. You are not competing to own a box, you are competing to be one of the sources the model draws on and to be described accurately when it does.
That changes the emphasis in three ways:
- Corroboration beats self-assertion. A synthesised answer weighs what multiple sources say. One very good page on your own domain is weaker evidence than consistent descriptions across your site, your profiles and independent coverage.
- Entity clarity becomes load-bearing. The model needs to know what kind of thing you are before it can decide you are relevant. Ambiguity about your name, category or service area suppresses you.
- Access is separately controlled. AI crawlers are governed by their own
robots.txtuser-agents. You can rank in Google and still be invisible to the systems writing the answers.
Where the work genuinely overlaps
Most of it:
- Crawlable, fast, well-structured pages
- Clear heading hierarchy and semantic HTML
- Accurate structured data consistent with visible content
- Content that actually answers the question asked
- Credible third-party mentions
If someone quotes you separately for “SEO” and “GEO” and the deliverables look largely identical, ask which specific tasks are unique to each. There are real ones, AI crawler access, prompt-level measurement, entity reconciliation, corroboration strategy but they are a minority of the total effort and they should be itemised rather than bundled as a second full-price retainer.
Where it genuinely differs
The measurement is the honest difference. Classic SEO is measured with rank tracking and Search Console. AI visibility has no equivalent authoritative data source. There is no “AI Search Console” reporting how often you were cited.
So measurement has to be constructed: define a prompt set, run it on a schedule across the assistants that matter to your buyers, record who gets named and how you are described and track the trend. It is more like survey research than rank tracking, sampled, noisy and only meaningful over time.
That is the part worth paying for, because it is the part that tells you whether any of the rest worked.
A note on scepticism
Nobody can guarantee a citation in any of these systems. They do not publish their ranking factors, they change frequently and results vary by user, region and session. Treat specific promises about placement in AI answers the way you would treat a guaranteed #1 ranking: as a reason to walk away.
If you want to start from measurement rather than from a package, our audit is built to do exactly that.
Further reading: What is answer engine optimization (AEO)?, What generative engine optimization actually involves and How to show up in Google AI Overviews and AI Mode.