More of your buyers are starting with a question to an AI instead of a list of blue links. They ask ChatGPT, Perplexity, or Google's AI Overviews, read the synthesized answer, and act on it. Often they never visit a website at all. That shift changes the job of marketing: you are no longer only trying to rank a page, you are trying to be the source the AI reads, trusts, and quotes.
Two terms describe this work. GEO, Generative Engine Optimization, is about getting your content used inside generated answers. AEO, Answer Engine Optimization, is about being the direct, citable answer to a specific question. In practice they overlap heavily, and most of the moves that help one help the other. Here is how these systems actually pick sources, and what you can do about it without inventing anything.
How AI answer engines choose what to cite
The mechanics differ by product, but the pattern is consistent. When you ask a question, the system usually does some form of retrieval first: it runs searches, pulls a set of candidate pages, and feeds the most relevant passages to a language model. The model then writes an answer grounded in those passages and, in tools like Perplexity and AI Overviews, attaches citations to the pages it leaned on.
A few things follow from that:
- Retrieval still depends on classic search signals. If a page can't be found and crawled, it can't be retrieved, and it can't be cited. Indexing, crawlability, and topical relevance still matter.
- The model favors passages it can lift cleanly. A clear sentence that directly answers the question is easier to quote than the same idea buried in a long, hedged paragraph.
- Corroboration helps. When several independent, reputable sources agree on a fact, a model is more comfortable stating it. Being one of those consistent sources increases your odds of being the cited one.
- Freshness and specificity matter for some queries. Dated, precise content tends to win time-sensitive questions.
You can't see the ranking function, and it changes often. So the honest goal is not to game a formula. It's to make your content the easiest correct thing to retrieve and quote.
Write so a machine can quote you
The single highest-leverage move is plain, factual writing. AI systems extract well-formed claims. Give them clean ones.
- Answer the question early. Lead a section with the direct answer, then explain. Don't make the reader, or the model, dig for it.
- Write self-contained sentences. A quotable line stands on its own without three sentences of setup. "A site's llms.txt file lists the URLs you most want AI crawlers to read" is liftable. "As we'll discuss, there's a file that, among other things, can be useful here" is not.
- Use real structure. Descriptive headings, short paragraphs, and lists make passages easy to isolate. Question-style headings that mirror how people actually ask tend to do well in answer engines.
- Define your terms. If you use a term of art, define it once, plainly. Models reuse clean definitions.
- Be honest about uncertainty. Don't fabricate precision. Vague-but-true beats specific-but-made-up, and made-up numbers get contradicted by other sources, which hurts you.
Avoid the temptation to stuff in invented statistics to sound authoritative. If a figure isn't real, you can't stand behind it, and AI systems increasingly cross-check claims against other sources.
Structured data, schema, and llms.txt
Plain writing gets you most of the way. A few technical signals help machines parse and trust your content.
- Schema markup. Structured data (Schema.org via JSON-LD) labels what a page is: an article, a product, an FAQ, an organization, a person. It doesn't guarantee a citation, but it removes ambiguity about entities and relationships, which makes your content easier to use correctly.
- FAQ and how-to structure. Even without formal schema, a genuine question-and-answer format maps neatly onto how people query answer engines.
- llms.txt. This is an emerging convention: a plain-text file at your domain root that points AI crawlers to the pages you most want them to read, often in clean Markdown. Support is still uneven across providers, so treat it as a low-cost, forward-looking signal, not a guarantee. It's cheap to add and it can't hurt.
- Clean, stable URLs and metadata. Accurate titles and descriptions still help both search retrieval and how your page gets summarized.
If you want help wiring schema, content structure, and the technical plumbing together, that's the kind of work we do under growth engineering.
Entity consistency and being a trusted source
Answer engines build a model of who you are across the web. Inconsistency confuses that model.
- Keep your facts identical everywhere. Company name, product names, what you do, where you operate, key claims about your offering. If your site, your profiles, and your listings disagree, the AI has to guess, and it may guess wrong or skip you.
- Be specific about your niche. "We build AI operational systems and custom software for small and mid-sized companies in Oklahoma and Texas" is a clearer entity than "we do digital solutions." Specific entities are easier to retrieve for specific questions.
- Earn corroboration honestly. Mentions, references, and links from credible places reinforce that you are a real, consistent source. This is slow, legitimate reputation work, not a trick.
- Publish things worth quoting. Original explanations, clear frameworks, and useful specifics give a model something to cite that competitors don't have.
How this relates to classic SEO
GEO and AEO don't replace SEO. They sit on top of it. Retrieval inside most AI systems leans on the same crawling, indexing, and relevance foundations search engines have always used. If your site is slow, blocked from crawlers, thin, or off-topic, you lose in both worlds.
The difference is the target. Classic SEO optimizes for a ranked list a human clicks through. GEO and AEO optimize for being read and quoted by a model that may answer without sending a click at all. That means you should care about two outcomes now: ranking well, and being citable when there's no click to win. Both still matter, and the work for each overlaps more than it conflicts.
Takeaway
You don't need a new playbook full of hacks. You need findable, well-structured, plainly written content that says true things clearly, a few sensible technical signals like schema and llms.txt, and consistent facts about who you are across the web. Do that and you make yourself the easiest correct source to quote, which is the whole game in AI answers.
If you want a concrete plan for your site, look at how we work or get in touch.