// Concept
What is Answer Engine Optimization (AEO)?
AEO is the older, narrower discipline of optimizing for direct-answer surfaces — featured snippets, voice assistants, and AI Overviews. GEO is its successor and superset.
// AEO vs GEO
AEO vs GEO: which one are you actually doing?
AEO came out of the 2017–2022 era of Google answer boxes: featured snippets, People Also Ask, knowledge panels, Alexa and Google Assistant. It assumed one engine (Google), one playbook (FAQ + HowTo schema, concise definitional copy), and one surface (the SERP). GEO assumes six engines, multi-turn conversation, and citations rather than answer boxes. If you are still talking about featured snippets without also tracking ChatGPT and Perplexity, you are doing AEO. If you are tracking citation share across every major generative engine, you are doing GEO. The right framing in 2026 is to treat AEO as one workstream inside a GEO program, not a competing discipline.
// Surface
What AEO covers.
- Featured snippets. The boxed paragraph or list Google promotes above organic results for definitional and instructional queries.
- People Also Ask. The expanding question stack on Google’s results page.
- Voice assistant answers. Whatever Alexa, Google Assistant, and Siri read out loud when asked a question.
- Knowledge panels. The entity card on the right rail; populated from your structured data, Wikipedia, and Wikidata.
- Google AI Overviews source cards. The cited-source row beneath the AI-generated summary. Same playbook, new surface.
// Blind spot
What AEO misses.
AEO frameworks were written for one engine. They have nothing to say about how Perplexity weighs source authority, how ChatGPT decides which three brands to name in a recommendation prompt, how Claude handles conflicting sources, or how the citation graph compounds across multi-turn conversations. The schema work AEO recommends still helps. The strategy it implies (rank for the snippet, win the answer) no longer describes the problem.
// Verdict
Should you still optimize for AEO?
Yes — but rename it. The schema markup, the concise definitions, the FAQ blocks, the HowTo structure all feed generative engines too. Keep the tactics. Drop the framing. Move your reporting from “do we own the snippet?” to “do the engines name us in answers?” That’s GEO with the AEO tactics still inside it. Vizelo tracks both layers in one place.
// Related
Keep reading.
FAQ
Common questions.
Is AEO the same as GEO?
No. AEO predates the generative-engine era and targets specific Google answer surfaces. GEO is broader: it covers AEO surfaces plus citation behavior across multi-turn AI engines like ChatGPT, Perplexity, and Claude. AEO is a subset of GEO.
Should you still optimize for AEO in 2026?
Yes, but think of it as one workstream inside GEO rather than a separate program. The FAQ schema, HowTo schema, and concise question-answer copy that lift AEO performance also feed the generative engines.
What does AEO actually cover?
Featured snippets, People Also Ask, voice assistant answers, knowledge panel population, and the source-card layer of Google AI Overviews. Anything where the engine returns a direct answer with a credited source.
What does AEO miss?
Cross-engine citation behavior. AEO frameworks were built around Google. They have nothing to say about how Perplexity weighs sources or how ChatGPT chooses which three brands to name when a user asks for recommendations.