AEO (Answer Engine Optimization)

Answer Engine Optimization (AEO) is the practice of structuring content so that answer engines return your page as the direct answer to a user's question. Answer engines here means Google featured snippets, People Also Ask, knowledge panels, AI Overviews, Bing answer boxes, and voice assistants. The unit of success is the extracted passage, not the ranked link.

The name dates to roughly 2014 to 2016, when Google began answering questions on the results page instead of only listing pages that might contain the answer. The tactics that won featured snippets then are the same tactics that win AI answers now. A question-shaped heading, a direct answer in the first 40 to 60 words beneath it, clean semantic HTML, FAQ markup where the content is genuinely a question and answer, and a visible date.

AEO is not GEO, and it is not SEO. The three differ in what they optimise and what they count as a win:

• SEO optimises a page to rank in a list of links. The win is a position. The user still clicks to read the answer.
• AEO optimises a passage to be extracted as the answer. The win is being the source the engine quotes. The user may never click.
• GEO optimises a page to be one of several sources an engine grounds a synthesised answer on. The win is citation share across a set of prompts, not a single position.

Put simply: SEO competes for a slot, AEO competes for the answer, GEO competes for a share of the answer. AEO is extraction-centric and usually single-source; GEO is grounding-centric and always multi-source. They share almost all of their underlying content hygiene, which is why running them as one programme is the pragmatic choice.

What changes in practice when a team adopts AEO. You write the answer first and the context second, which inverts the usual article structure. You stop hedging, because a qualified, conditional sentence is not extractable. You give every question its own heading rather than burying three answers in one section. You date and review pages on a schedule, because recency is a selection signal. You add FAQ and HowTo markup only where the content really is a question or a procedure, since stuffed schema is now devalued rather than rewarded. And you accept that a successful AEO page can lose click-through while gaining influence, so the reporting has to change alongside the writing.

The category boundary keeps blurring. Google AI Overviews and Bing Copilot extract for short factual questions and synthesise across sources for complex ones, so the same page is being judged by both mechanisms on different queries. Most practitioners now use AEO for the extraction subset, GEO for the multi-source generative subset, and run one content baseline underneath both.