The acronyms arrived faster than the explanations. Here is the short version, with the overlaps admitted rather than papered over.
- SEO optimises to be ranked in a list of links.
- AEO optimises to be the answer — the snippet, the voice reply, the one-line response.
- GEO optimises to be cited inside a generated answer written by a language model.
- The term GEO comes from a 2024 peer-reviewed paper at KDD by researchers at Princeton, IIT Delhi and Georgia Tech, which was the first controlled study showing content can be deliberately optimised for AI-generated answers.
SEO — be on the list
Search engine optimisation assumes a results page: ten links, ranked. The work is keywords, links, crawlability, page speed. The measurement is position, and position maps to clicks.
The assumption underneath is that the user will choose. Your job is to be in the choice set and look attractive.
AEO — be the answer
Answer engine optimisation predates the current AI wave. It grew out of featured snippets and voice assistants, where there is no list — Siri reads one answer aloud, and second place does not exist.
The work changes shape: structure your content as questions and answers, mark it up so machines know which part is the question, and answer plainly enough to be quoted verbatim.
The assumption underneath is that the machine will choose, and it will choose once.
GEO — be in what the model writes
Generative engine optimisation deals with systems that retrieve several sources and then write something new from them. Nobody is quoting you verbatim. A model is reading you alongside your competitors and synthesising.
The 2024 KDD paper defined the generative engine as a system that retrieves documents from an index and uses a large language model to synthesise a grounded response. Crucially, the researchers then tested nine content modifications to see which ones increased a source's visibility in the generated answer.
Their reported findings are the useful part:
- Adding verifiable statistics, credible quotations and citations to reliable sources produced the largest gains — on the order of 30–40% on their visibility metric.
- Improving fluency and readability produced smaller but still meaningful gains, roughly 15–30%.
Read that again, because it is unusual. The things that made content more visible to a generative engine are the things that make it more credible to a human editor: cite your sources, use real numbers, write clearly. This is a rare case where gaming the system and doing good work point the same direction.
So which term is right?
Honestly, the industry has not settled, and you should be suspicious of anyone who claims it has. AEO and GEO are used interchangeably by many practitioners. A reasonable way to hold them:
- AEO is about the retrieval layer — being the source that gets selected for a specific fact.
- GEO is the wider discipline — everything about how you appear across generative systems.
The label matters far less than the shift underneath it, which is this: you are no longer optimising for a ranking. You are optimising to be the material an answer is built from.
Frequently asked
Do I need to do all three?
They are not three separate projects. Being crawlable serves all three. Writing clear question-and-answer content serves AEO and GEO at once. The genuinely new work is making sure your facts — prices, hours, what you actually do — exist somewhere machine-readable rather than only inside a PDF or an image.
Can anyone guarantee I appear in an AI answer?
No. Assistants are operated by other companies, and they decide what to retrieve and what to write. Their models and retrieval behaviour change without notice. Anyone promising a placement or a rank in an AI answer is promising something they do not control. What can be done is to make sure accurate, well-structured information about you exists where these systems look.
Is this just SEO with new branding?
Partly, and it is fair to be sceptical. The overlap is real: crawlability, structure and credibility mattered before and matter now. What is genuinely new is that the output is synthesised rather than listed, so the unit of success moves from a link to a sentence.
- Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan, Deshpande, GEO: Generative Engine Optimization, KDD 2024 — arXiv:2311.09735
- Princeton University research listing for the same paper
The 30–40% and 15–30% figures are the paper's own reported gains on its position-adjusted visibility metric, measured on its test set. They are not a promise of the same result on any given site.