AEO, answer engine optimization, is search engine optimization pointed at a reader that quotes instead of ranks. Most of the work carries over unchanged. Two things shift. Competition narrows to a single written answer, often a sentence or two, and text other people write about you, above all your customer reviews, carries more of the weight. The page-level work you already do for search is most of the job, and the part that's new sits largely outside your own website.
What's the difference between AEO and SEO?
SEO is the long-standing practice of shaping your website so a search engine ranks it high on a list of links. AEO is the newer name for shaping your presence so an AI model, the software behind ChatGPT, Gemini, Perplexity, and Google's AI Overviews, picks your business out and describes it accurately when someone asks a question in plain words.
The difference is the reader. A search engine hands a person ten options and lets them choose. An AI model reads the options itself, writes one answer, and sometimes names one business. On a ranked list, being third is fine. In a written answer, there's often no third.
| SEO | AEO | |
|---|---|---|
| Unit | The page | The answer, often a sentence or two |
| Reader | A person scanning a list of links | An AI model that reads, summarizes, and quotes |
| Strongest signal | Your own pages and the links pointing at them | Your pages plus what others write about you, reviews especially |
| Measurement | Rankings, clicks, and traffic in Search Console | Asking the AI apps a fixed set of questions on a schedule and reading what comes back |
The measurement row is the uncomfortable one, and we wrote up how we measure it on our own site, including why the dashboards you already have can't see most of it.
What carries over from SEO?
Nearly all of it. Google says so directly in its guidance on AI features in Search, which states that there are no additional requirements to appear in AI Overviews or AI Mode and that SEO best practices remain relevant. That's worth taking at face value, partly because it saves money. A vendor selling you a separate AEO package built on secret techniques is selling something Google says doesn't exist.
What carries over is the dull, durable stuff. A site that loads on a phone. Pages that say plainly what you do and where. A name, address, and phone number that match everywhere they appear. A complete Google Business Profile, with hours that are right in February and right in July.
The first of the two real changes is about shape. An AI model lifts an answer, so a page that states its answer in the first paragraph, under a heading phrased the way a customer would ask it, gives the model something to take. A plumber's page that opens with three paragraphs about the company's founding gives it nothing. That's a writing habit, and the part of AEO you control alone.
The second change is about who's doing the talking, and it's the bigger one.
Why do reviews matter more in AI answers?
Google's own Maps features summarize reviews with Gemini, so what customers write now carries more weight than it did on a ranked list. Getting more of those reviews, and what AI answers do with them, is the subject of why reviews now write your AI search answer.
How is AEO measured differently?
SEO comes with instruments. Search Console tells you which queries showed your pages, where you ranked, and how many people clicked. AEO has nothing like that yet. Many AI answers send no click, so traffic reports miss them, and no AI company publishes a ranking report for your business.
What's left is the plain method in the table. Write down a fixed set of questions your customers would actually ask, put them to the main AI apps on a schedule, and record who gets named and in what words. It's slow and a little manual, and the answers wobble from one day to the next, so a single check means little and a run of them over months means a lot. The inputs are steadier to track. Check whether your pages lead with the answer, whether your listings match, and whether recent reviews keep arriving, because those are the levers and the answer is the lagging result.
What a review record says about your business, read as data, is in why your star rating is the last page.
Where this sits in the bigger picture
In the four levels of using AI in your business, this post sits on the far side of Level 1. Your customers are the ones asking, and the model is answering from whatever record you left it. You don't have to use AI at all for this to apply to you.
The work itself is mostly the marketing baseline, the same profile, consistency, and reviews checklist that served search before AI models read it, and it's the core of what our marketing work covers.
What nobody can tell you yet is how much any single review moves an answer, or how long a model keeps reading an old one. Google publishes what its features do, not how they weigh things, and the other products publish less. Until one of them does, is a business optimizing for an answer engine, or just doing good SEO and hoping the model is paying attention?