Four names circulate for roughly one practice: answer engine optimization, generative engine optimization, AI SEO and LLM SEO. Marketing teams keep getting asked which one they do.
The short answer: the four names describe overlapping work and separate audiences. This piece sets out where each term came from, what Google’s results pages say about them, and which one to put on a page.
What is generative engine optimization?
Generative engine optimization, or GEO, means improving how a brand shows up inside AI-generated answers. It covers the same ground as answer engine optimization, or AEO. Both aim to make your pages the source an assistant quotes.
GEO is the biggest of the four terms by search volume. It draws 8,100 monthly searches in the United States at a Semrush keyword difficulty of 87. AEO draws 3,600 at difficulty 65 (Semrush, us database, August 2026).
Difficulty of 87 puts the head term out of reach for a new site. The question phrasings around it stay open. The “what is” version carries 1,900 searches. “Is GEO the same as traditional SEO” carries 90 at difficulty 27. “Why is GEO important” carries another 90 at difficulty 28.
When did the term GEO emerge?
The term comes from a 2023 academic paper. Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande submitted “GEO: Generative Engine Optimization” to arXiv on 16 November 2023 (arXiv:2311.09735).
The paper introduced a benchmark called GEO-bench. Its abstract reports that the methods “can boost visibility by up to 40% in generative engine responses”. People quote that 40% constantly and rarely quote its context.
Two things about the context matter. The paper tested content methods, such as adding quotations, adding statistics and citing sources. It never tested structured data or markup of any kind. Anyone citing it as proof that markup drives AI citations has misread it.
AEO has no comparable origin document. It grew out of practitioner usage. That is part of why nobody has cleanly separated the two terms.
Is answer engine optimization and generative engine optimization the same?
In practice they describe the same work. No authority has drawn a line between them. Wikipedia puts it directly: “Other terms for the same concept include answer engine optimization (AEO), large language model optimization (LLMO), artificial intelligence optimization (AIO), and AI SEO.”
The same article records that no consensus definition separating these terms existed in the academic literature as of early 2026, and that people use them interchangeably (Wikipedia).
Google’s results pages disagree. That is the part with a practical consequence.
We pulled the top 12 organic results for “answer engine optimization”, “generative engine optimization” and “llm seo” on 8 August 2026 (Semrush, us database). Not one URL appears on more than one of the three lists.
Set Reddit and YouTube aside and only three brands appear on two of the three: Coursera, Forbes and HubSpot. Each time they rank with a different page written for the different term. Google’s own guidance page ranks first for GEO and never appears in the top 12 for the other two.
So the concepts overlap and the results pages do not. A page written for one term does not compete for the others.
What does GEO mean in SEO?
In current results, GEO reads as the generative meaning rather than the geographic one. The abbreviation used to belong to local and international SEO. Search has displaced that reading.
The results page shows it. The top 10 for “geo seo” on 8 August 2026 includes Google’s AI optimization guide, Wikipedia’s GEO article, a Coursera course on mastering GEO, and two “GEO vs SEO” explainers (Semrush, us database).
“Geo seo” carries 2,900 monthly searches at difficulty 66. If your business does local search work, that term no longer brings you the audience it used to.
What is LLM SEO?
LLM SEO names the same practice after the technology rather than the interface. LLM stands for large language model, the kind of system behind ChatGPT and Claude.
It is the smallest and softest of the four terms. LLM SEO draws 1,300 searches a month at difficulty 35. AI SEO sits at difficulty 74 and GEO at 87 (Semrush, us database, August 2026).
Its results page has a distinct character. The top 12 for “llm seo” holds practitioner blogs and independent tools almost exclusively. No encyclopaedia entry, no analyst piece and no Google documentation appear.
“AI SEO” reads differently again. Tool pages and tool roundups dominate its top 10, so the market treats that phrase as software that does SEO using AI rather than as a practice.
Why is generative engine optimization important?
It matters because more buyer research now ends in a written answer than in a list of links. Pew Research Center found that 18% of Google searches in its March 2025 sample produced an AI summary. Users clicked a search result on 8% of visits where a summary appeared, against 15% where none did (Pew Research Center, 22 July 2025).
The visibility gap behind that is wide. Webflow analysed more than 2,000 US company websites. The median company appeared in 16% of the answers to questions a typical prospect would ask. It earned a link 6% of the time (Webflow AEO Maturity Index).
Our own panels point the same way. Between 14 and 31 July 2026 we ran a fixed question set across ChatGPT, Perplexity, Gemini and Claude for six B2B companies. That produced more than 340 recorded answers. In three of the six, no engine named the company in any answer to an unbranded question.
Which term should a marketing team actually use?
Use the spelled-out term your buyers type, and pick one per page. Mixing all four names into a single page splits its relevance across four results pages that share no URLs.
Our own working rule runs three lines:
- Write “answer engine optimization (AEO)” in full. The bare acronym is unusable. “AEO” alone draws 22,200 searches a month. Its results page belongs to the clothing retailer American Eagle Outfitters and to Authorised Economic Operator, a customs status (Semrush, us database, 8 August 2026).
- Use “generative engine optimization” for a technical or analyst audience. The academic paper, Wikipedia and Google’s documentation all sit there.
- Treat “AI SEO” as a tools query. If you do not sell software, that results page is not for you.
None of the naming changes the work. Google’s position holds whatever label you use: “optimizing for generative AI search is optimizing for the search experience, and thus still SEO” (Google Search Central).
What do the four names have in common?
All four describe the same three jobs: get found, get quoted, get named. The vocabulary changes and the work underneath it does not.
Every version asks for the same structural things. Phrase the heading as the question a buyer types. Answer it in the first sentence beneath. Keep one company name across your markup, your titles and your copy. Put a real person’s name on the page.
The one genuine difference sits in measurement. Google publishes documentation and gives you Search Console. ChatGPT, Perplexity and Claude publish neither, so you have to ask them directly and record what comes back.
That is why we treat the naming as a titling decision rather than a strategy decision. Pick the term your buyer types, then measure across every engine regardless of what you called the page.
Frequently asked questions
How does generative engine optimization work?
It works by making pages easy to quote and brands easy to identify. In practice that means four things: headings phrased as the questions buyers ask, a direct answer in the first sentence under each heading, one company name used consistently across your markup and your copy, and a named author on every page.
Is generative engine optimization a part of SEO now?
Google treats it as continuous with SEO on its own surfaces and says no special optimisation is needed for AI Overviews or AI Mode. Assistants that run their own retrieval, such as ChatGPT and Perplexity, are not bound by that. The safe reading: GEO is SEO plus a measurement layer for engines Google does not control.
How do I improve my GEO?
Measure it first, because most teams have no baseline. Put 15 to 20 unbranded buyer questions to ChatGPT, Perplexity, Gemini and Claude on a fixed date. Record which brands each engine named and which domains it cited. That number is the one you move.
Are there risks to using generative engine optimization?
The main risk is spending on tactics nobody has evidenced. Several widely repeated figures in this field trace back to blog posts with no disclosed method, no sample size and no control group. Ask for the source of any number a vendor quotes before you budget against it.
Search volumes and results-page data are Semrush, us database, August 2026, with results pages pulled on 8 August 2026. Client observations come from our own visibility panels and are reported without naming clients. Public sources are linked where used.