What is Answer Engine Optimization (AEO)?
Answer Engine Optimization (AEO) is the practice of structuring content so it gets selected as the direct answer in AI assistants, featured snippets, and AI Overviews, not merely as one of several sources. AEO rewards a clear question heading, a concise two-to-three-sentence answer immediately beneath it, and schema markup that makes the structure machine-readable.
Answer Engine Optimization (AEO) is the discipline of formatting content so it is selected as the answer, the response read aloud by a voice assistant, displayed inside a featured snippet, or shown as the synthesized result in a Google AI Overview, rather than as one of many ranked sources.
What AEO targets
- Featured snippets
- The boxed answer that appears above standard organic results, pulled from pages Google considers authoritative. Google’s systems determine whether a page would make a good featured snippet and, if so, elevate it.
- AI Overviews & AI engine citations
- AI engines extract answers more efficiently from short, dense, well-organized content with schema markup than from long content where the answer is buried. Pages that already perform well for featured snippets tend to be cited at higher rates by Perplexity and ChatGPT Search as well.
- Voice assistant answers
- Strong entity signals: Wikidata entries, Knowledge Panels, schema markup, let voice assistants identify and read back the correct answer source.
How to optimize for AEO
- Lead with the question as a heading, place an exact-match question in an
<h2>or<h3>. - Answer in two to three sentences immediately below, self-contained, no preamble.
- Use schema markup: FAQPage, HowTo, Article, or Organization schema makes the structure machine-readable for search and AI engines.
- Include factual specificity, concrete numbers, dates, and named entities make content more citation-worthy.
- Cite authoritative sources within the text, adding citations and statistics significantly boosts source visibility in AI engine results.
Relationship to GEO
AEO predates the term Generative Engine Optimization (GEO), which emerged in 2024 as the AI search category formed. GEO extends AEO principles to generative AI systems that synthesize multi-source answers. Internally, the same approach is sometimes called writing for the extract.
Last reviewed: 19/05/2026