AEO vs GEO: what's the difference?
Two acronyms for the same shift, with a useful distinction underneath. Here's how they fit together.
Everything about how a brand is represented inside generated output.
The part that decides whether you are named in the answer.
If you've started reading about AI search, you've hit two acronyms that seem to mean the same thing: AEO and GEO. They overlap heavily, and plenty of people use them interchangeably. But there's a distinction worth keeping.
AEO — Answer Engine Optimization
AEO focuses on the outcome: showing up, accurately, in the answer an engine produces. It's outcome-first — mentions, recommendations, citations, and correctness in the response a buyer actually reads.
GEO — Generative Engine Optimization
GEO focuses on the input: shaping your content and your presence so a generative model can understand, trust, and reuse it. It's about being legible to a model — clear structure, unambiguous facts, and authority signals the model can pick up on.
How they fit together
Think of GEO as the work and AEO as the scoreboard. You do GEO — clarify your content, earn trustworthy citations, fix the technical gaps — and you measure AEO, whether that work actually moved how often and how well AI names you. Brand Climb covers both: it measures the answer and hands you the input-side moves most likely to change it.
Why the distinction is worth keeping
Because they belong to different people and run on different clocks. The GEO work is content, PR and engineering: rewriting an ambiguous page, earning a place on a review site, fixing what a crawler cannot read. The AEO measurement is analytics: it tells you whether any of that landed. Teams that collapse the two tend to keep shipping input-side work with no way of knowing which parts mattered — which is how content programmes run for a year on faith.
The trap in measuring only one
Measure only AEO and you have a number that moves for reasons you cannot attribute — an engine updated, a competitor published something, or your own work finally landed, and you cannot tell which. Do only GEO and you are optimising blind. The pairing is what makes either useful: change one input deliberately, then watch the specific questions it should have affected.
A third acronym you can ignore
You will also see LLMO, AI SEO, and a few others. They describe the same shift with different emphases, and none of them changes what you should actually do: find the questions that decide purchases in your category, measure how the engines answer them, fix what you can control, and check whether the answer changed. The vocabulary will keep moving; that loop will not.