AEO Glossary: AI Search Terms Explained in Plain English

Your agency just told you your citation rate grew 12% last quarter. You nodded along … but you have no idea what that actually means … and you’re worried it shows.

If this sounds familiar, don’t worry — you’re not behind. This is a space that is growing so fast, the entire marketing industry hasn’t even agreed on its own vocabulary yet.

We’re here to help you navigate this evolving world with a glossary of AI search-related terms. Bookmark this post so the next time you see one of these phrases in a strategy or report, you can quickly come here to understand what it means — rather than nodding along and hoping it all makes sense later.

Let’s dive in!

What are we optimizing for?

It’s always good to start at the beginning, and in this case, that means understanding where we want your content to show up. There are several ways this can happen in the world of AI.

LLM (large language model): The type of AI system behind tools like ChatGPT, Claude, Gemini, and Copilot. LLMs are trained on enormous amounts of text, and they generate their responses by predicting what should come next. Their answers are based on their training and, increasingly, real-time information the model retrieves from the web.

Answer engines: A catch-all term for the tools people now use to get direct answers, rather than a traditional search engine results page. Answer engines can mean AI chat tools like ChatGPT and Perplexity, as well as AI-powered features built directly into search engines, like Google’s AI Overviews.

Google AI Overviews: The AI-generated summary box that appears at the top of a regular Google search results page for many queries. Google draws from multiple sources to synthesize a direct answer, which it places above the traditional list of links.

Google AI Mode: A separate, more conversational Google feature, distinct from AI Overviews. Rather than a summary box on a normal search results page, AI Mode replaces the search results with its own dedicated space where you can have an extended back-and-forth conversation with Google, asking follow-up questions like you would with a chatbot. (For more on Google AI Overviews versus AI Mode, see this AI Mode explainer from CBS News.)

Zero-click search: A search that provides the answer directly on the results page, through an AI Overview, a featured snippet, or a similar element, without requiring you to click through to any website at all. Zero-click search isn’t new, but AI-generated answers have accelerated it.

What do we call this new kind of optimization?

One of the trickiest parts about this space is that we don’t all agree on what to even call it. This is a real, ongoing debate in the marketing industry, and there are many terms to describe the process of optimizing content for LLM platforms. All of them are similar but slightly different — although the similarities are close enough that you can safely use all the terms interchangeably, and your agency team will know what you mean.

AEO (Answer Engine Optimization): This term refers to optimizing content so an answer engine presents it as a direct answer, such as a featured snippet, a voice assistant response, or an AI-generated summary. In other words, AEO is about becoming the specific answer to a specific question.

AIO (AI Optimization): This term refers to optimizing content for all AI systems, but it can also more specifically refer to optimizing for Google’s AI Overview section on the search engine results page.

GEO (Generative Engine Optimization): This term refers to optimizing content so generative AI tools such as ChatGPT, Claude, Perplexity, or Gemini can understand it well enough to cite it in a generated response. There is a huge overlap between GEO and AEO. The distinction some practitioners draw is that AEO targets the answer itself, while GEO targets being one of the sources the answer draws from.

LLMO (large language model optimization): This term is the broadest of the four and refers more generally to how a brand shows up when an AI platform recommends products or vendors, not just when answering a search query.

Again, all of these terms are used somewhat interchangeably. If your agency uses one term and a guru you follow on LinkedIn uses another, that’s not a sign one of them is wrong. It simply shows that the vocabulary hasn’t caught up to the work yet.

What terms might be in a strategy proposal?

When an agency is describing the technical and structural work involved in preparing your site and content for AI systems, they may use the following terms.

Structured data/schema markup: Extra code added to a webpage that explicitly labels what different pieces of content mean. For example, schema can be used to tell the LLM a section of content is describing a product, or a review, or an FAQ, etc., so the LLM doesn’t have to guess or infer it from context. This helps the LLM know how to use the content.

Entities: A specific, identifiable thing (such as a company, a person, a product, a concept) that a search engine or AI system can recognize and connect to other information about it. Strong entity recognition is part of why AI systems can confidently attribute a specific fact to your company by name, rather than describing it vaguely.

E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness): A framework Google uses to evaluate whether your content demonstrates real, first-hand knowledge of a topic. This is an established SEO concept that’s now even more relevant — because just like search engines, AI systems are also trying to figure out which sources to trust. Google explains the E-E-A-T concept in more detail on its own Search Central blog.

Crawlability for AI bots: Whether your site is accessible to the automated bots that AI platforms use to read and index web content. Note that this is different from how traditional search engine bots crawl a site. But for both AI and SEO platforms, if your site accidentally blocks these bots at the technical level, your content will be invisible — no matter how good it is.

llms.txt: A newer type of file, similar to the long-standing robots.txt file, that gives AI systems a curated map of your website’s most important content. While it’s intended to make it easier for AI models to find and understand what actually matters on your site, it’s still an emerging standard, and adoption is uneven. Notably, Google has stated in their AI Optimization Guide that llms.txt files won’t hurt your site — but it won’t help your site, either.

Content chunking: Structuring content in clearly separated, self-contained sections (for example, by providing a distinct answer to a distinct question, rather than one long flowing narrative) so an AI system can extract relevant sections without needing the whole page for context.

What terms might be in a report?

It’s very likely your agency is sending you reports that include metrics that didn’t even exist a few years ago! Here are some terms you’re probably seeing.

LLM extractability: How easily an AI system can pull clear, accurate information out of a piece of content and use it correctly in a generated answer. Some agencies (including Clariant Creative!) now run an LLM extractability check on content before it publishes; it’s similar to running an SEO check on a draft before it goes live, except this version is checking for LLM comprehension rather than keyword optimization.

Share of voice/AI share of voice: In traditional marketing, share of voice measures how often your brand shows up in a space relative to competitors. The AI version measures how often your brand gets mentioned or cited across AI-generated answers to relevant questions, compared to your competitors being mentioned for the same questions.

Citation rate: How often an AI system cites or references your content as a source when answering a question. This is the closest AEO equivalent to traditional search ranking. However, the bar is very high — only a small fraction of indexed domains get cited in AI Overviews at all, according to this Search Engine Land analysis.

Brand mention tracking: Monitoring how often your brand name shows up in AI-generated answers, whether or not the mention includes a link back to your site. This matters because AI answers frequently mention sources but don’t include links. This is also a major real shift from how backlinks work in traditional SEO.

Prompt testing (or prompt sets): Running a defined, repeatable list of realistic questions through AI tools on a regular basis to see whether, and how, your brand shows up in the answers. This is how an agency actually measures AI visibility over time, since there’s no single dashboard equivalent to a search rank tracker yet. If a report references “our monthly prompt testing,” this is what that means.

Referral traffic from AI platforms: A newer segment inside your website analytics showing visits that originated from an AI tool (e.g., someone clicked a link inside a ChatGPT or Perplexity answer). For most companies, this number is still relatively small compared to other traffic sources, but it’s one of the only direct traffic signals that AEO work produces.

How does all this compare to regular SEO?

Traditional SEO has always been about one thing: Making sure the right people can find your content when they’re looking for something. That part hasn’t changed. But what has changed is where and how the “finding” happens.

Here’s a useful way to think about it: SEO gets you found. AEO, AIO, and GEO help you become part of the answer, even when the reader never clicks through to your site at all.

That last point is the one that trips people up, and it’s driving a major shift in both content strategy and content performance measurement: It’s entirely possible for your content to be doing its job (getting cited, building trust, shaping the answer a prospect sees) without a single visit showing up in your website analytics. “Performance” in this scenario means something entirely new, and it’s why your agency may start showing you metrics you haven’t seen before.

One more thing worth knowing: None of this replaces SEO. The foundational work of technical SEO — including the need for quality content and a sound site structure — is still important. These elements are still what enable the LLM platforms to crawl your web pages, understand your content, and hopefully cite your brand in their answers.

In other words. AEO, AIO, and GEO don’t replace SEO; they build on it.

How to use this glossary

Please don’t worry about trying to memorize every term we’ve shared here. Honestly, it’s not even possible right now, since the industry keeps adding new terms all the time.

Instead, we hope you can use this page as a helpful reference point when you need it. So the next time your agency mentions citation rate, or a proposal references an llms.txt file, or a report includes some new metric you’ve never seen before, just pull up this post.

After all, that’s the real value of a shared vocabulary: That you’re never stuck figuring it out alone.

Want a practical next step? Download our AIO Action Plan Checklist for a 10-point rundown of how to start implementing all this.