What's the Difference Between GEO and AEO?

Updated 19 October 2026 · 6 min read · By Matthew Bertram

Nobody owns either term. You'll hear them swapped freely, and that does little harm because the page work is the same. The difference changes a decision in one place: the settings that let AI systems use your content for training or for live answers. Even there, Google's controls don't follow the line the two labels draw.

Where did the term GEO come from?

From a research paper. In November 2023, six researchers posted "GEO: Generative Engine Optimization" to arXiv, the open archive where researchers post papers, and it was later accepted to KDD 2024, a major data mining conference. Its stated aim was "to aid content creators in improving their content visibility in generative engine responses."

Visibility, in that paper, meant citation: both of its measures scored the sources a generated answer cited, one of them by counting the words attributed to each source, adjusted for where in the answer they appeared. So GEO began as a citation discipline, which is the job AEO is usually given. The paper's best-known number is also its most misquoted, so read what the GEO paper measured before you repeat a figure from it.

Neither term has settled since. Guests on this show have defined GEO five different ways in five episodes. AEO has no founding paper that we know of. It grew out of SEO practice.

Isn't GEO the same as local SEO?

No. In marketing, "geo" has long meant location, as in geotargeting or geofencing, and local SEO is about ranking for searches tied to a place. Generative engine optimization has nothing to do with geography. When a proposal lists GEO, ask which one it means before you agree to pay for it.

Where do GEO and AEO split?

At the citation. AEO is judged by a visible source: did the answer link to your page or not? GEO also covers the answers that cite nothing, where a model writes about your business from what it learned in training.

That isn't the line the GEO paper drew, since the paper measured only citations, but it's the line this guide uses because it's the one that changes what you check.

Why does the training layer change things?

It runs on a slower clock. A page an engine fetches live can be cited as soon as the engine has crawled it. What a model learned in training changes only when a new version of the model is trained and released, and you can't test a change against it in the meantime. AEO sits in the live layer. GEO, as this guide uses it, spans both.

Which settings control which layer?

Each company draws the line in its own place. Check its documentation, not the label. Three examples:

• OpenAI splits the two cleanly. Its crawler documentation says OAI-SearchBot crawls to surface sites in ChatGPT's search features, while GPTBot collects content that "may be used in training" its models. OpenAI adds: "Each setting is independent of the others." You can allow one and block the other.
• Perplexity keeps its main crawler out of training. PerplexityBot "is not used to crawl content for AI foundation models," according to Perplexity's documentation.
• Google splits it two ways, and not only along the training line. Google-Extended, a robots.txt token, controls whether Google can use your content to train future Gemini models and to ground answers in the Gemini app, which means handing the model pages from Google's index at the moment someone asks. That's live retrieval, the layer AEO depends on. Google says it "does not impact a site's inclusion in Google Search." AI Overviews and AI Mode have their own switch, the Search generative AI control in Search Console, which Google rolled out to all sites on August 31, 2026. Google's on-record position is that this switch "doesn't affect AI training."

So at Google, a site that blocks Google-Extended to stay out of AI is still eligible for AI Overviews. A site that switches off AI Overviews hasn't opted out of training. Our guide to blocking AI crawlers goes through the decision one user agent at a time.

These are three companies' published rules as of October 2026. Anthropic and Microsoft publish their own, which this guide doesn't cover.

How do you measure GEO and AEO?

AEO now has first-party numbers. GEO has none.

On Google, Search Console's generative AI performance report shows your site's impressions in AI Overviews and AI Mode over time, broken down by page, country and device, but it can't tell you which searches triggered them. Google says AI Overviews may run more searches than the one a person typed, and our guide to how AI Overviews choose their sources explains that step. Microsoft goes further. Bing Webmaster Tools' AI Performance report counts how often Copilot and Bing's AI summaries cite your pages, and it shows a sample of the "grounding queries" behind those citations. For ChatGPT and Perplexity, you ask the questions yourself and record the sources.

GEO has no report, because there's no citation to count. You ask each assistant about your business and read what it says. Answers change from one run to the next, so a single check proves little. Our guide to checking whether AI engines cite you covers how many repeats a reading needs, and descriptions need the same repeats.

Do you need a separate GEO strategy?

For most businesses, no. The page work is the same for both, and our guide to answer engine optimization lists it. Split it into two workstreams and you pay for one task list twice.

Two cases deserve their own attention. The first is the settings decision above. It's the one place where the training layer and the answer layer can be treated differently, so make the choice on purpose instead of keeping whatever a template or plugin set.

The second is a business where a wrong description costs real money. Think of a medical practice or a financial adviser, which work on topics Google calls "Your Money or Your Life" because bad information about them can hurt people, or a company whose name another company shares. Those businesses need to check what assistants say about them, not only whether they're cited.

What if an AI describes your business wrong?

Fix the sources it learns from. We know of no assistant that lets a business submit a correction and have the model's description changed. So the work is indirect.

Make every page and profile you control tell the same story about who you are and what you do. Correct the third-party pages that get it wrong. Then get the right version stated somewhere credible that you don't control, such as an industry directory or a trade publication. Schema markup gets pitched as the fix here too, and our guide to schema and AI citations covers what it does and doesn't do.

Expect it to be slow. Answers that search the web can pick up a corrected page once it's recrawled, but a description that comes from training changes only when the model is retrained, and you can't schedule that.

Want to hear how ChatGPT, Gemini and Perplexity describe your company when their answers show no sources? Book a discovery call with EWR Digital →

Keep reading: What Is Answer Engine Optimization (AEO)? · Should I Block AI Crawlers in Robots.txt? · How Do I Know If ChatGPT or Google AI Overviews Are Citing My Site?

Have you been quoted for GEO and AEO as two separate services? Send us the scope of work, with the prices taken out if you like. We'll mark which line items are the same task under two names, and add what we find to this guide.