Semrush analysed 126 million U.S. prompts from January to April 2026 and found ChatGPT leaned on about 15 sources per answer, while Gemini used about 3. (Semrush) Put the same question about your brand to both and you're dealing with two very different editors. Generative engine optimization (GEO) is the work of shaping what AI systems write about your brand: whether AI assistants and AI search summaries include you in a generated answer, and whether the sentence they write about you is accurate.
If that sounds a lot like AEO, it is, and we'd argue you shouldn't buy them separately. The terms overlap heavily, and the biggest search engine treats both as SEO. The useful difference is one of emphasis. AEO starts from the buyer's question. GEO starts from the paragraph the model generates.
This page explains where the term came from, why there are several names for similar work, what GEO focuses on in practice for a B2B SaaS company, and which GEO pitches to be wary of. For the question-led side, read the pillar on what AEO is. For how both relate to classic search, see AEO vs SEO.
Where the term "GEO" came from
The engines in question include ChatGPT, Gemini, Perplexity and Google's AI Overviews, and Google treats both AEO and GEO as SEO. The name comes from research. A paper titled "GEO: Generative Engine Optimization", by Pranjal Aggarwal and co-authors, first posted to arXiv in November 2023, used the term for methods that help content show up in answers written by generative search systems. (arXiv) It's a 2023 paper, so it's cited here only for where the name comes from. Its results predate today's engines and say nothing about how they behave now.
Since then, agencies and tool vendors have adopted the label, often with different meanings. On X, the arguments over whether GEO is "just SEO" have run all year. In May 2026, Joe Davies wrote that Google had "just released guidelines basically saying AEO + GEO is SEO as usual," and that SEOs arguing over the label were missing the point. (Joe Davies on X)
GEO, AEO, LLM SEO: one goal, different starting points
Google's guide to its generative AI features treats AEO and GEO as descriptions of the same work as SEO for those features: pages must be indexed and able to appear in Search with a snippet, with no extra technical requirements, per Google. (Google Search Central, AI features and your website) That's the official view, and it's a fair one for Google's own products.
Agencies still split the work, because the jobs start in different places. The table shows how Miraa uses the terms. Other agencies draw the lines differently.
Term | Starts from | Main question |
|---|---|---|
SEO | The query and the ranking page | Can this page be crawled, indexed and ranked? |
AEO | The buyer's question | Does one of our pages answer it cleanly enough to be cited? |
GEO | The generated paragraph | When a model describes us, is it accurate and are we included? |
LLM SEO | The model's understanding of the site | Can a model explain us from our crawlable pages at all? |
Miraa's GEO page puts it this way: GEO is "the work of being summarized without being distorted," and "the generated paragraph is the surface." (Miraa)
You don't need four programs. Most engagements touch all four. The table is useful mainly for working out which problem you actually have.
What GEO focuses on in practice
For a B2B SaaS company, GEO comes down to one question: when someone asks an AI assistant about your category, what does it say about you? Four things shape that answer.
1. A description you can stand behind
Write down the one or two sentences you'd want a model to repeat: what you are, who it's for, and the limits that matter (the segment you don't serve, the integration you don't have). If your team can't agree on those sentences, a model won't either.
Then check whether your own site says the same thing everywhere. Homepage, pricing page, docs, comparison pages and old blog posts often disagree. The GEO agency roundup on this blog puts the risk plainly: conflicting pages lead to summaries that blend them, sound sure of themselves, and get it wrong. (Miraa blog)
2. Pages a model can actually read
If the system never retrieved a fact, the answer can't contain it. When pricing appears only after JavaScript runs, features sit behind a login or crawlers can't reach the docs, the model guesses to fill the gap. Google's AI features also require the site to be opted in to Search Console's "Search generative AI" setting. (Google Search Central)
3. What other sites say about you
Models don't only read your domain. Ahrefs' study of 75,000 brands found that YouTube mentions (about 0.737) and branded web mentions (0.66 to 0.71) correlated more strongly with AI visibility than anything else it measured, while the number of pages on a site barely mattered (about 0.194). (Ahrefs) Correlation isn't proof, but it suggests a GEO program that only edits your blog is working half the problem.
For B2B SaaS, the third-party sources that tend to shape descriptions are review sites, integration partner listings, analyst and press coverage, community threads, and other vendors' comparison pages. Some are yours to update. Others you can only ask to correct.
4. Different engines, different paragraphs
Engines don't agree with each other. In that same Semrush index, citation overlap fell below 50% for every pair of platforms. (Semrush) So "what AI says about us" is really several answers, and each needs checking.
A simple GEO check you can run this week
You can see your GEO problem in an afternoon:
Pick five prompts a buyer would ask near a decision, such as "best [category] tool for [segment]" and "[competitor] alternatives".
Ask each prompt in ChatGPT, Perplexity, Gemini and Google AI Mode.
For every answer that mentions you, copy the sentence about you into a sheet.
Compare each sentence with the description you wrote down. Mark it correct, partly wrong or wrong.
For each error, note where it probably came from: an old page of yours, a third-party listing, or a competitor's comparison page.
That sheet is your first GEO backlog. Fixing your own pages comes first, then asking third parties to update theirs. When you want to repeat the check properly, with a fixed prompt set, repeated runs and trends over time, see the guide to measuring AI search visibility.
GEO pitches to be wary of
Because the term is new, a lot of what's sold as GEO is either ordinary SEO with a new label or something riskier.
Getting you "into the training data". Miraa's GEO page says it has no access to a model's training set, and if someone offers to insert you into a training corpus, "that is a different pitch." (Miraa) Ask any vendor how they would do that.
A separate "GEO blog" or a page for every prompt. Per Google's guide, publishing a page for each variation of a query "primarily to manipulate rankings or generative AI responses" is scaled content abuse in its terms. (Google Search Central)
Paid placements in AI answers or bought mentions. Google lists seeking inauthentic mentions among tactics that aren't as helpful as they seem. (Google Search Central) In September 2026, Glenn Gabe wrote that a publisher selling AI visibility to brand partners would amount to "inauthentic mentions." (Glenn Gabe on X)
Special files and formats as the fix. Google says its Search systems ignore llms.txt and that you don't need to "chunk" content for its AI features. (Google Search Central) Other services may use such files, but they won't repair an inaccurate description.
Guaranteed citations. No one controls a specific generated answer. Miraa's GEO page points to its pricing FAQ and AEO page, which both say inclusion in a specific generated answer isn't for sale. (Miraa)
Does your company need GEO?
GEO is worth prioritizing when AI answers are already part of how buyers find you and the answers are wrong or leave you out. Signs include prospects on sales calls repeating something an AI tool told them that isn't true, competitors named for your core category prompt while you're missing, or AI answers describing a feature you retired or a price you changed.
If your pages aren't being indexed or ranked, start with SEO. If buyers' questions have no clear answer on your site, start with AEO. If the answers exist but the AI's description of you is off, that's GEO.
If you're comparing outside help, the roundup of generative engine optimization agencies compares ten on published method, measurement, pricing and recent reviews. B2B SaaS teams focused on question-level work can also look at the list of AEO agencies for B2B SaaS, and AI product companies at the list of AEO agencies for agentic AI companies.
Two sentences to start with
GEO is a new label for an old discipline pointed at a new surface: the paragraph a model writes about you. Google says the fundamentals are the same as SEO, and for its own products that's right. What GEO adds is the habit of reading those paragraphs, checking them against what's true, and fixing the sources they come from.
Don't start with a tool or an agency. Write the two sentences you want AI to say about you, run the five-prompt check above, and fix the source pages behind any answer that gets you wrong. Only pay for GEO help once you know what the errors are.
Miraa's generative engine optimization page describes how it approaches the work.