SEO, AEO, and GEO are three separate jobs. SEO gets your page ranked in a list of results. AEO gets your brand named, accurately, inside the AI answer buyers actually read. GEO shapes the sources a model pulls from so your brand is built into the text it writes. They overlap, but they are not the same thing with fresh labels, and treating them as one is where most teams go wrong.
SEO: rank a page in a list
SEO is the oldest of the three and the most understood. The job is to get a specific page to rank high in a list of search results for a query. Success is a position: page one, top of the list, a featured snippet.
The reader still does the work. They see a set of links, choose one, and click through to your site. SEO optimizes for that click. It cares about relevance, crawlability, page quality, and links pointing at the page.
None of this goes away. Ranked, crawlable pages are the raw material the newer jobs depend on. But ranking is where SEO stops. It puts your page in the running. It does not decide what a machine says about you afterward.
AEO: earn a named place inside the answer
AEO is answer-engine optimization. The job is to be named, accurately, and well sourced inside the single reply an AI answer engine writes for a question. The unit is not a rank. It is a mention.
This matters because an answer engine does not hand back a list. It reads a few sources, composes one response, and names a short set of brands inside it. If you are not in that set, the reader may never learn you exist for that question, no matter how well a page of yours would have ranked.
So AEO asks a different set of questions. Are you present in the answer at all? Is what the engine says about you correct? Is it citing a source you would stand behind? Presence, accuracy, and sourcing are the three things AEO works on, and a page can rank well while failing all three.
GEO: shape the sources a model reads
GEO is generative-engine optimization. The job is to influence the material a model pulls from at the moment it writes, so your brand ends up woven into the generated text and cited as a source.
Where AEO measures the outcome (were you named, and correctly), GEO works upstream on the inputs. It asks which pages, mentions, and reference sources a model is likely to draw on for a topic, and whether your brand is well represented across them. That includes your own content, but also the third-party pages, comparisons, and references a model tends to trust.
The two are close, and they are often discussed together. A useful way to hold them apart: AEO is about the answer you get, GEO is about the sources behind it. Improve the sources and you improve the odds of the answer. Measure the answer and you learn whether the source work paid off.
Where they overlap
These jobs are not walled off from each other. The clearest overlap runs through Google. Its AI Overviews are generated on top of search, so the pages that rank are also the pages that feed the answer. Weak SEO there means weak raw material for the AI response. Strong SEO gives the newer jobs something to work with.
The same pattern holds more broadly. Ranked, well-structured, quotable pages are easier for a model to read, trust, and lift from. Good SEO does not guarantee a mention, but poor SEO makes one harder. This is why the two are best treated as a stack, not as rivals: SEO feeds AEO, and the sources SEO helps produce are part of what GEO shapes.
The overlap is also where the confusion starts. Because the jobs share inputs, it is tempting to assume that doing one does the others for free. It does not. Ranking a page and being named in an answer are different outcomes, measured in different places, and a win in one does not certify a win in the next.
Why you need all three, measured together
Each job covers a gap the others leave open, so a program that runs only one has a blind spot. SEO alone tells you where your pages sit in a list, and nothing about what machines say. AEO alone tells you whether you are named, but not why, so you cannot act on it. GEO alone shapes sources without confirming the answer ever changed.
Put together, they form one loop. Rank your pages so they are in the pool a model can read. Check that you are actually present and accurately described in the answers buyers see. Shape the surrounding sources so you are more likely to be cited. Then look at the answers again to see whether any of it moved.
Measuring them together is what keeps that loop honest. A page can rank while the answer ignores it. An answer can name you while getting a fact wrong. A source push can go in without the reply changing at all. You only see these gaps when rank, mention, accuracy, and citation sit side by side. Watch one number and you are optimizing part of a system while missing the rest of it.