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What is AEO (Answer Engine Optimization)? Definition and business implications
AEO (Answer Engine Optimization) is a sub-discipline of GEO, focused on producing direct answers to user questions. It targets answer engines (Google AI Overviews, ChatGPT, Perplexity) that require a concise, sourced response, restituable as is, rather than a page to browse.
AEO differs from GEO by its focus on interrogative queries (“what is”, “how”, “why”, “how much”). Three practices structure AEO. The opening answer sentence: every page dealing with a question must start with a short self-contained response (one or two sentences), immediately extractable. Google sets no ideal length: this is an editorial convention, not a requirement. This sentence is the easiest for answer engines to extract and cite. FAQ markup: Schema.org FAQPage and Question/Answer blocks make question-answer pairs explicit for search engines and AI systems. This markup no longer guarantees any enhanced display: Google stopped showing FAQ rich results on 7 May 2026, and states that no special markup is required for its generative AI features. It remains useful for the machine readability of the page. Factual pertinence: an AEO response must be quantified when possible, sourced when the topic is sensitive, and regularly revised. An obsolete data point is worse than missing data: the engine cites the erroneous data and engages the editorial responsibility of the source site.
Concrete example
Illustrative case. A 60-employee legal expertise firm overhauls in 2025 its expertise pages by topic: 80 pages in total. Three AEO adjustments. Each page begins with a short answer sentence to the title question (“What does case law say on imposed remote work?”). FAQPage markup is added in JSON-LD. Pages are updated quarterly. Six months later, the firm is cited in 14 AI Overviews responses per month on average, against zero before. The queries generating these citations do not all produce clicks, but the firm appears as a source in the responses themselves.
FAQ
What is AEO and how does it differ from GEO?
AEO (Answer Engine Optimization) is a sub-discipline of GEO, focused on producing direct answers to user questions. It is set apart by its focus on interrogative queries ('what is', 'how', 'why', 'how much') and targets answer engines that require a concise, sourced response, restituable as is.
How do you structure a page for AEO?
Three practices. An opening answer sentence (short, self-contained, immediately extractable; Google sets no ideal length), the easiest to cite. FAQ markup (Schema.org FAQPage and Question/Answer). Factual pertinence: a response quantified when possible, sourced when the topic is sensitive, and regularly revised.
Does FAQ markup still produce an enhanced display?
No. Google stopped showing FAQ rich results on 7 May 2026 and states that no special markup is required for its generative AI features. The markup remains useful for the machine readability of the page.
Why update pages regularly?
Because Google describes systems that retrieve relevant, up-to-date pages: on topics that change, regular revision reduces the risk of being cited with outdated data. An obsolete data point is in fact worse than missing data, because the engine cites the erroneous data and engages the editorial responsibility of the source site.
Which content actually gets cited?
Precise content is easier to reuse. Vague, generic, or purely marketing content gives little to cite. Quantified, sourced content that clearly addresses a question gives more, with no guarantee of citation.
See also
Further reading
Sources
- Schema.org official specifications, FAQPage and Question, 2026. https://schema.org/FAQPage
- AI Overviews documentation, Google Search Central, 2025. https://developers.google.com/search/docs/appearance/ai-features
- Google's Guide to Optimizing for Generative AI Features on Google Search, Google Search Central, 2026. https://developers.google.com/search/docs/fundamentals/ai-optimization-guide
- Google Search Central, documentation updates log: FAQ rich result discontinued (7 May 2026) and llms.txt note (June 2026). https://developers.google.com/search/updates