AEO and GEO Explained: What Helps a Site Appear in AI Search?
By Evan Weber7 min read
AEO and GEO are names for making useful website content easier to discover and understand in answer and generative search experiences. For Google AI features, the work still begins with ordinary SEO: an accessible page, helpful content, a clear topic and eligibility to appear in Search with a snippet.
There is no file, schema type or writing formula that guarantees a citation. Google's current AI search guidance says its generative search features draw on core Search systems and advises site owners to create original, useful content. That is the starting point for this guide and our AEO and GEO training.
What AEO and GEO mean
Answer Engine Optimization often refers to making a page answer a question clearly enough to be useful in search answers. Generative Engine Optimization refers to visibility when an AI system summarizes or cites sources. The labels describe an outcome, not a separate set of technical requirements shared by every search provider.
A useful page can give a direct answer near the top, then explain the conditions, evidence and next action. The answer still has to be accurate and useful for a person who clicks through.
Start with access and the right page
Check that the intended URL returns its own content, title and canonical in the initial HTML. Confirm that robots rules, meta robots and server responses allow the page to be crawled and indexed. A page that returns the homepage HTML for every article URL needs its routing fixed before another article is added.
Map each meaningful question to one useful page. If someone wants to choose a training provider, give them scope, delivery, price path and a contact or booking action. If they want an explanation, answer it before asking them to book. Separate pages should serve distinct tasks, not minor wording variations.
Add evidence people can use
Original examples, a worked comparison, screenshots of a real process, limitations and an accountable author can make a page more useful than a generic summary. Link to primary sources for product and search claims that can change. Keep those sources current when the page is updated.
Use structured data only when it accurately represents visible content and is supported for the intended search feature. Google's guidance does not require a special AI schema, a prescribed chunk size or llms.txt for its AI search features. A maintained llms.txt file can still be useful for other readers or systems, but it is not a Google ranking requirement.
Measure discovery separately from results
Use Search Console to compare queries, pages, impressions and clicks before and after a change. Check indexed status and the live URL when a page fails to appear. If an AI product sends referral traffic, label it separately from ordinary organic search and connect it to qualified leads when possible.
Citation spot checks are observations. Record the engine, question, locale, date and cited URL. A single answer with or without your site does not establish a citation rate. If you need help deciding what to fix first, AI search training can use your own pages as the working material.
Key takeaways
- For Google AI search, useful original content and ordinary Search eligibility remain the foundation.
- Fix page routing, crawlability and intent match before adding more markup or articles.
- Measure indexing, search traffic, AI referrals and qualified leads as separate outcomes.
Frequently asked questions
Does GEO replace SEO?
No. For Google AI search, the same core search and quality systems apply. Other providers may use different retrieval systems, so check their own documentation and your actual referral data.
Do I need llms.txt to appear in Google AI search?
No. Google says its Search systems do not use llms.txt as a special requirement for generative AI features.
Will FAQ schema make an AI cite my page?
No. Structured data should match visible page content and meet feature policies, but markup alone does not guarantee indexing, a rich result or an AI citation.
Evan is a 25-year digital marketing veteran, founder of Experience Advertising, and a daily Claude Cowork and Codex user who trains business teams to use agentic AI fluently in their real workflows.
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