Answer engine optimization is structuring content so an engine can extract a direct answer from it: a question heading, the answer in the first sentence, lists and tables, FAQ markup. It was built for featured snippets and voice. The same structure is what AI engines quote today, which is why AEO has been absorbed into GEO rather than replaced by it.
The definition, AEO against GEO, which techniques still work, and the one voice habit worth keeping.
Answer engine optimization (AEO) is the practice of structuring content so that a search engine can extract a direct answer from it, originally for Google's featured snippet and voice assistants. It called for a question-form heading, a concise definition or answer in the first sentence beneath it, lists and tables for procedures, and FAQ markup. The term dates from about 2014. In practice it has been absorbed into generative engine optimization, which asks for the same structure and adds entity resolution and four-engine measurement.
The term is still searched, which is why this page exists, and vendors still sell it as a distinct service, which is why this page says what it says. A buyer asked to choose between an AEO vendor and a GEO vendor is being asked to pay twice for one piece of work. The useful question for either is how they measure the four engines, and whether separately.
AEO targeted a single extracted answer, the featured snippet or a voice response, on one engine. GEO targets a composed answer across several AI engines that may cite several sources at once. The content structure each asks for is nearly identical. What GEO adds is entity resolution, so the engine can place the company, and separate measurement across ChatGPT, Gemini, AI Mode and AI Overviews, because they disagree.
The one real change is in the last two rows. A snippet was a single box on a single query, won or lost. A generated answer is composed from a fan-out of sub-queries and may name three companies and cite six pages. Being present for the sub-queries, not only the headline term, is new work. So is the measurement, because a company can win the Google answer and be absent from ChatGPT's. The GEO vs SEO page sets out the overlap by engine.
All of the structural ones. A question-form heading with a direct answer beneath it is still what every engine quotes. A definition in the first sentence is still what gets extracted. Numbered steps and comparison tables are still lifted whole. FAQ markup that matches the visible questions still helps the engine resolve what the page answers. What no longer works on its own is optimizing for one box on one engine and calling the job done.
Less than it did, because voice assistants have largely been absorbed into the same generative systems. A question asked of Google Assistant or Siri now routes through the same AI answer layer as a typed query, and the content that gets read aloud is the content that gets cited in text. Optimizing for voice separately is no longer a distinct job; it is a side effect of being quotable.
The one voice-specific habit worth keeping is the speakable markup: a SpeakableSpecification in WebPage schema pointing at the headline, the lede and the lead answers. It costs nothing, it is on every page of this site, and it tells any engine that reads aloud which passages were written to be read that way.
Figures described as measured are from Search Standing's own analyses using Semrush, Google Search Console and direct queries to each AI engine, on the dates stated. Published ranges move quarter to quarter; the patterns are what we rely on.
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