AEO, short for answer engine optimization, is the work of getting your brand and your pages into the answer when someone asks a search engine or an AI assistant a question. The goal isn't a higher spot in a list of links. It's being picked as the answer. In practice AEO means almost the same thing as GEO (generative engine optimization), and both sit on top of ordinary SEO.
Key takeaways
- AEO predates generative AI. It was coined around 2017 to 2018, when featured snippets and voice assistants started answering questions directly. Today it covers ChatGPT, Google AI Overviews, AI Mode and Naver AI Briefing.
- GEO comes from a 2023 research paper on visibility inside generative AI answers. The two terms now cover the same ground.
- Google's 2026 guidance says plainly that, from Google Search's perspective, AEO and GEO are still SEO.
- The real difference is the unit of success. SEO counts rankings and clicks. AEO and GEO count mentions and citations inside answers.
- A sensible order: build a question list, measure today's answers, publish pages that answer, earn genuine outside mentions, then measure again under the same conditions.
Where did the term AEO come from?
SEO consultant Jason Barnard is generally credited with coining "answer engine optimization" in 2017 or 2018. Google had begun answering questions directly, in answer boxes at the top of results and through voice assistants, and being chosen as that answer became a goal of its own, separate from ranking.
GEO arrived later. The paper "GEO: Generative Engine Optimization", by researchers from Princeton, IIT Delhi and others, was posted in November 2023 and published at KDD 2024. The authors found that adding citations to sources, relevant quotations and statistics could raise a source's visibility in generative engine answers by up to 40%.
In Japan you'll also hear LLMO (large language model optimization) and "AIO" for the same work. Different labels, same goal: get your brand into what the AI says.
How do AEO, GEO and SEO differ?
| SEO | AEO | GEO | |
|---|---|---|---|
| Emerged | Late 1990s | 2017 to 2018 | 2023 |
| Original target | Lists of search results | Featured snippets, voice answers | Generative answers in ChatGPT, Perplexity |
| Target today | Search results, plus the pages AI answers draw on | AI Overviews, AI Mode, ChatGPT, Naver AI Briefing | Same as AEO |
| Unit of success | Rankings, impressions, clicks | Mentions, citations, recommendations in answers | Mention rate, citation rate, share of voice |
| Typical work | Crawling and indexing, keywords, links, page quality | Question-led content, direct answers up top, FAQs | Measuring answers per engine, pages that get cited, outside mentions |
AEO and GEO now aim at the same screens, and most of the industry uses them interchangeably. At Anymorph we call the whole thing AI search optimization. Our GEO explainer goes deeper on the definitions.
What does Google say about AEO?
Google addressed both terms directly in its 2026 guide to generative AI features in Search. Its position: optimizing for generative AI search is optimizing for the search experience, and so it's still SEO. That follows from how AI Overviews and AI Mode work. They pull pages from Google's core ranking systems and build the answer from them.
The same guide lists things you don't need to do: AI-specific files like llms.txt, chopping content into small chunks, rewriting pages just for AI, collecting inauthentic mentions, and special AI-only structured data. What it does stress is content that doesn't just repeat what's already out there. First-hand experience and real expertise, it says, will matter more over time than anything else in the guide.
That's right for Google. But AI search isn't only Google. ChatGPT search draws on OpenAI's own crawler and third-party search providers, and in Korea, 70% of what Naver AI Briefing cites comes from Naver's own blogs, cafes and Q&A. Each engine pulls from a different pool, so Google SEO alone can't explain every engine's answers. We compare them in Where AI search engines get their answers.
So what's actually new in AEO?
If the foundation is SEO, what changes? Measuring AI answers for brands every day, we see four differences.
- You measure answers, not rankings. The same question gets different answers across engines and across days. Instead of a rank tracker, you read answers repeatedly and record mentions and citations.
- You design questions, not keywords. People ask AI full, situational sentences, not two or three words. A set of prompts to measure replaces the keyword list.
- Outside sources matter more. AI answers cite reviews, communities, media and blogs more often than brand sites. Pages you don't control become part of the job.
- Every engine has its own door. Which crawlers you allow in robots.txt, and which search index you're in, decide whether you're even a candidate in a given engine.
How to start with AEO
- Build a question list. Write 30 to 100 questions your customers would ask AI. Mix category questions ("best CRM for a 10-person team"), comparisons ("A vs. B"), problems and brand checks. Anymorph Analyze builds this list from brand knowledge and search demand.
- Measure today's answers. For each question, record what ChatGPT, Gemini, Google AI Overviews and AI Mode, Perplexity and, for Korea, Naver AI Briefing say. Note whether your brand appears, in what position, which sources are cited, and how competitors fare.
- Publish pages that answer. Look at the page types answers cite most (comparison tables, guides, pricing, FAQs) and build pages on your own site that answer each question precisely. Put the answer in the first paragraph, and add tables, numbers, sources and an updated date.
- Earn genuine outside mentions. Get real customers and experts talking where AI looks: reviews, communities, press, blogs. Google says chasing inauthentic mentions doesn't help.
- Measure again, the same way. Ask the same questions of the same engines on the same schedule, and see which changes moved the answers.
What to look for in an AEO tool or agency
- Engines covered. Does it measure the engines your customers use, including regional ones like Naver?
- Raw answers. Does it show the actual answer text and cited sources, not just a score?
- Repeated measurement. Is it a one-off audit, or does it re-run the same questions on a schedule?
- Execution. Does it stop at reports, or also build and publish pages?
- Overpromising. Google warns against tools that guarantee rankings or claim access to internal Google metrics. "Guaranteed #1" can't be verified.
FAQ
Which term is correct, AEO or GEO?
Both. AEO came from the featured snippet and voice era, GEO from the generative AI era, but they describe the same work today. Use whichever your team and customers use.
If I do AEO, can I skip SEO?
No. Google AI Overviews and AI Mode pull sources from Google's index, and Naver AI Briefing from Naver's. If crawling, indexing and page quality are broken, you won't even be a candidate for AI answers.
How long until AEO shows results?
New pages take days to weeks to get indexed, and answers move at different speeds for different engines and questions. Re-measure the same questions under the same conditions for at least one to two months before drawing conclusions.
Are LLMO and AIO different from AEO?
They're terms common in Japan. LLMO stands for large language model optimization; AIO usually refers to AI Overviews or AI optimization. The target and the work are the same as AEO and GEO.
Sources
- Google Search Central, Optimizing your website for generative AI features on Google Search
- Aggarwal et al., GEO: Generative Engine Optimization (KDD 2024)
- Jason Barnard, SEO Was Always Answer Engine Optimization (March 2026)
- NAVER, CDO Kim Kwang-hyun Reveals Data & Content Strategy for the AI Era (May 2026)