This glossary covers every term you need to understand when optimizing your content for AI-powered search engines. If you are working on Generative Engine Optimization, tracking how ChatGPT or Perplexity cite your website, or just trying to figure out what "AI visibility" actually means, this is your reference. The field is moving fast, new vocabulary is forming every quarter, and most of the terms below did not exist two years ago. We built this GEO glossary at GetCited because we kept seeing the same confusion: marketers and founders using terms loosely, mixing up concepts, or missing critical terminology entirely. Every definition here is written to be clear, specific, and useful whether you are brand new to GEO or already running optimization campaigns.

The terms are organized alphabetically. Each entry includes what the term means, how it works in practice, and why it matters for your AI search visibility. Bookmark this page. You will come back to it.

A

AI Citation

An AI citation is a reference that an AI-powered search engine includes in its response to attribute information to a specific source. When ChatGPT, Perplexity, or Gemini answers a question and links to your website as the source of a statistic, definition, or recommendation, that link is an AI citation. Citations can appear as inline hyperlinks, footnotes, or listed sources at the bottom of an AI-generated response.

AI citations are the currency of Generative Engine Optimization. In traditional SEO, a ranking on page one was the goal. In GEO, the goal is getting cited. A single citation in a ChatGPT response about a high-intent topic can drive more qualified traffic than a top-five Google ranking for the same query. The critical difference is that users who click an AI citation have already been told by the AI that your source is worth reading.

AI Crawlers

AI crawlers are automated bots deployed by AI companies to discover, access, and index web content for use in training data, retrieval-augmented generation (RAG), or real-time search. The major AI crawlers active in 2026 include GPTBot and OAI-SearchBot (OpenAI), PerplexityBot (Perplexity), ClaudeBot (Anthropic), Google-Extended (Google/DeepMind), and Bytespider (ByteDance/TikTok). Each crawler has a unique user agent string that appears in your server logs and can be managed through your robots.txt file.

Understanding AI crawlers is foundational to any GEO strategy. If you are blocking these bots, your content cannot be retrieved and cited by the AI engines they power. Many websites accidentally block AI crawlers through overly restrictive robots.txt rules, and they wonder why ChatGPT never mentions them. Monitoring which AI crawlers are accessing your site, how frequently, and which pages they visit gives you direct insight into how AI engines perceive your content.

AI Overviews

AI Overviews are Google's AI-generated summaries that appear at the top of search results for a growing number of queries. Powered by Gemini, these summaries synthesize information from multiple web sources and present a conversational answer before any traditional organic results. As of early 2026, AI Overviews appear in up to 60% of Google searches depending on query category. See also: Google AI Overviews.

AI Overviews have fundamentally changed what it means to "rank on Google." Even if your page ranks #1 organically, the AI Overview sits above it and answers the question before the user ever scrolls. Getting your content cited within an AI Overview is now more valuable than the traditional #1 position for many informational queries. This is where GEO and SEO intersect most directly.

AI Search Visibility

AI search visibility is the degree to which your brand, content, or website appears in AI-generated responses across platforms like ChatGPT, Perplexity, Google AI Overviews, Claude, and Gemini. It encompasses whether your brand is mentioned, how often it is cited, whether links point back to your domain, and the sentiment of how AI engines describe you.

This is the metric that connects all of GEO together. You can think of AI search visibility as the AI equivalent of "organic visibility" in traditional SEO. The difference is that AI visibility is harder to track because there are no stable rankings to monitor. Your visibility can change based on how a question is phrased, when it is asked, and what sources the AI engine retrieves in that moment. Tools like GetCited exist specifically to measure and track AI search visibility across multiple engines.

AI Visibility Score

An AI visibility score is a composite metric that quantifies how visible a brand or domain is across AI-powered search platforms. The score typically accounts for citation frequency, citation consistency across question variations, the number of AI engines citing the brand, and source attribution quality. There is no single industry-standard formula yet, but the concept is becoming central to how teams measure GEO performance.

AI visibility scores give teams a single number to track over time, similar to how domain authority functions in traditional SEO. Without a visibility score, you are left manually querying AI engines and eyeballing whether your brand shows up. That does not scale. As the GEO space matures, expect AI visibility scores to become as standard as keyword rankings.

Answer Engine Optimization (AEO)

Answer Engine Optimization is an alternative term for Generative Engine Optimization that emphasizes the shift from search engines to answer engines. AEO focuses on optimizing content so that AI-powered tools can extract and present it as direct answers to user questions. The term predates GEO slightly and was initially used to describe optimization for Google's featured snippets, but it has expanded to cover all AI answer platforms.

AEO and GEO refer to the same core practice. The term "AEO" resonates with marketers who think of ChatGPT and Perplexity as "answer engines" rather than "generative engines." If you see AEO in an article or job description, assume it covers the same territory as GEO. The Princeton research paper that formalized the discipline used "GEO," which is why that term has broader academic and industry adoption.

Article Schema

Article schema is a specific type of structured data markup (using Schema.org vocabulary) that tells search engines and AI crawlers detailed information about a piece of content: its headline, author, publication date, last modified date, publisher, and description. It is implemented in JSON-LD format and placed in the <head> section of a webpage.

For AI visibility, article schema serves as a machine-readable ID card for your content. AI crawlers use this structured data to understand what a page covers, who wrote it, and how current it is. Pages with properly implemented article schema are easier for AI engines to parse, categorize, and cite. If your content lacks article schema, you are making AI engines guess at metadata they could otherwise read directly.

B

Bytespider

Bytespider is the web crawler operated by ByteDance, the company behind TikTok. It crawls web content for multiple purposes, including training AI models and powering content recommendations. Bytespider is one of the more aggressive crawlers in terms of request volume, and many publishers choose to block it.

From a GEO perspective, Bytespider matters primarily if you care about visibility in ByteDance's AI products or if its crawling is consuming excessive server resources. Most GEO strategies prioritize GPTBot, PerplexityBot, and ClaudeBot over Bytespider, but you should still be aware it exists and make a conscious decision about whether to allow or restrict its access.

C

Citation Rate

Citation rate is the percentage of relevant AI queries for which your brand or content is cited as a source. For example, if there are 50 common questions in your industry and ChatGPT cites your website when answering 10 of them, your citation rate for ChatGPT is 20%. Citation rate can be measured per AI platform, per topic cluster, or across all AI engines combined.

Citation rate is arguably the most important metric in GEO. It tells you, in concrete terms, how often AI engines consider your content worth referencing. A low citation rate means your content is either not being crawled, not authoritative enough, or not structured in a way that AI engines can extract and cite. Tracking citation rate over time shows you whether your GEO efforts are actually working.

CITE Framework

The CITE Framework is a structured methodology for optimizing content for AI search visibility. CITE stands for Credibility, Information density, Timeliness, and Extractability. The framework provides a systematic approach to evaluating and improving content across the four dimensions that most strongly predict whether AI engines will cite it.

The CITE Framework matters because it gives practitioners a repeatable process instead of ad hoc guessing. Credibility covers author expertise, source citations, and E-E-A-T signals. Information density addresses the fact-to-word ratio and data specificity. Timeliness focuses on content freshness and update frequency. Extractability deals with structure, schema markup, and how easy it is for AI engines to pull quotable statements from your content.

ClaudeBot

ClaudeBot is the web crawler operated by Anthropic to retrieve content for Claude, Anthropic's AI assistant. When Claude answers a question using web search, ClaudeBot fetches pages in real time to provide current information. Its user agent string identifies it as "ClaudeBot" in server logs and robots.txt directives.

ClaudeBot access matters if you want your content to appear in Claude's responses. Claude is increasingly used in professional and enterprise settings, making it a valuable channel for B2B visibility. Allowing ClaudeBot in your robots.txt ensures your content is available when Claude performs web retrieval. Blocking it means Claude cannot access your pages when generating real-time answers.

Content Citability

Content citability is a qualitative measure of how likely a piece of content is to be selected and cited by an AI engine. Citable content typically features clear definitions, specific statistics, direct answers to common questions, original data, and well-structured formatting. Content with high citability reads like something an AI engine would want to quote directly.

Citability is a concept GetCited uses to help teams evaluate their content before publication. The question is straightforward: if an AI engine were answering a question your content addresses, would it choose your page as the source? Content that is vague, opinion-heavy, or lacks concrete claims has low citability. Content that leads with clear answers, backs them with data, and organizes information under descriptive headings has high citability.

D

Domain Authority (in AI Context)

Domain authority, in the context of AI search, refers to the overall trustworthiness and credibility that AI engines assign to a domain. While traditional domain authority (as measured by Moz, Ahrefs, or Semrush) is based heavily on backlink profiles, AI engines weigh domain authority differently. They consider factors like how often a domain is cited in training data, whether authoritative sources reference it, and the consistency and accuracy of the information it publishes.

Here is the important nuance: high traditional domain authority does not automatically translate to high AI visibility. Research has shown that AI engines sometimes cite lower-authority domains over higher-authority ones if the lower-authority content is more specific, data-rich, and directly answers the query. Domain authority still matters for AI visibility, but it is not the dominant factor it is in traditional SEO. This is good news for newer sites with exceptional content.

E

E-E-A-T

E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness. Originally a framework from Google's Search Quality Rater Guidelines, E-E-A-T has become equally relevant to AI search visibility. AI engines evaluate whether a content creator has direct experience with a topic, demonstrated expertise, recognized authority, and a track record of producing trustworthy information.

For GEO, E-E-A-T signals function as credibility markers that influence whether AI engines select your content for citation. Pages with clearly identified authors who have verifiable credentials, content that references primary sources, and domains with established reputations in their niche score higher on E-E-A-T. Practical steps include adding detailed author bios, linking to author credentials, citing original research, and publishing on a domain that has a consistent topical focus.

F

FAQ Schema

FAQ schema is structured data markup that identifies question-and-answer pairs on a webpage. Implemented using JSON-LD with the FAQPage schema type, it explicitly tells search engines and AI crawlers which questions your content answers and what those answers are. Each Q&A pair is marked up with the Question and Answer properties.

FAQ schema is one of the highest-impact technical optimizations for AI visibility. When an AI engine crawls a page with FAQ schema, it can instantly identify the questions covered and extract the corresponding answers. This makes your content dramatically easier to cite. Pages with FAQ schema are essentially handing AI engines pre-formatted, question-matched answers on a silver platter.

G

Generative Engine Optimization (GEO)

Generative Engine Optimization is the practice of optimizing web content so that AI-powered search platforms cite, reference, and recommend it in their generated responses. The term was introduced in a 2023 research paper by Aggarwal et al. from Princeton University, Georgia Tech, the Allen Institute for AI, and IIT Delhi. GEO encompasses content strategy, technical markup, crawler management, and measurement practices designed specifically for AI search engines.

GEO is the defining discipline of this glossary and, increasingly, of digital marketing in 2026. Traditional SEO optimized for a list of ten blue links. GEO optimizes for an AI-generated answer that may cite zero, one, or a handful of sources. The stakes per citation are higher because there are fewer slots, users trust AI-curated sources more than they trust self-selected search results, and the share of search traffic flowing through AI engines is growing by 30-40% year over year. If SEO was about getting on page one, GEO is about getting into the answer.

Google AI Overviews

Google AI Overviews are the AI-generated summary blocks that appear at the top of Google search results pages. Powered by Google's Gemini model, these overviews pull information from multiple sources, synthesize it into a coherent answer, and display it prominently above the traditional organic results. Google has been expanding AI Overviews aggressively, and they now appear in a majority of informational queries.

Google AI Overviews represent the bridge between traditional SEO and GEO. Because they appear within Google Search itself, they affect organic click-through rates directly. Pages that are cited within an AI Overview may actually gain traffic, while pages that are not cited but rank organically below the overview may lose significant traffic. Optimizing for AI Overviews requires many of the same GEO techniques: clear answers, structured data, high citability, and authoritative content.

Google-Extended

Google-Extended is the user agent token that Google uses for crawling content specifically for AI training and Gemini. It is separate from Googlebot, which crawls for traditional search indexing. By configuring your robots.txt to allow or disallow Google-Extended, you can control whether your content is used for Google's AI products without affecting your traditional Google search indexing.

This distinction is critically important and widely misunderstood. Blocking Googlebot blocks your content from Google Search entirely. Blocking Google-Extended only blocks your content from being used for AI training and Gemini responses. Many publishers who want to maintain Google search rankings but opt out of AI training will block Google-Extended while allowing Googlebot. If you want to appear in Google AI Overviews, you should allow Google-Extended access.

GPTBot

GPTBot is OpenAI's web crawler, used to discover and retrieve content for ChatGPT and other OpenAI products. It is identified by the user agent string "GPTBot" in server logs and robots.txt configurations. GPTBot crawls content that may be used for both model training and real-time retrieval when ChatGPT performs web searches.

GPTBot is the single most important AI crawler for most GEO strategies because ChatGPT has the largest user base of any AI search platform. If your robots.txt blocks GPTBot, your content will not appear in ChatGPT's web search results and cannot be cited in real-time responses. Allowing GPTBot access is typically the first technical step in any GEO implementation.

Grounding (Gemini)

Grounding is Google's term for the process by which Gemini anchors its responses in real-world, verifiable information retrieved from the web. When Gemini "grounds" a response, it performs real-time web retrieval to find current sources that support its answer, then cites those sources. Grounded responses are distinguished from purely generative responses by the presence of source citations.

Grounding matters for GEO because it defines when and how Gemini cites external content. Not every Gemini response is grounded. Factual, time-sensitive, and specific queries are more likely to trigger grounding. Optimizing for grounded Gemini responses means ensuring your content is accessible to Google-Extended, is factually current, and provides the kind of specific, verifiable information that Gemini seeks when it grounds an answer.

J

JSON-LD

JSON-LD (JavaScript Object Notation for Linked Data) is the recommended format for implementing structured data on web pages. It uses a script block in the HTML <head> to provide machine-readable information about the page's content, author, organization, and other entities. Google, AI crawlers, and other systems parse JSON-LD to understand page content without relying solely on visual interpretation.

JSON-LD is the technical backbone of structured data for GEO. When you implement article schema, FAQ schema, organization schema, or any other Schema.org markup, JSON-LD is how you deliver it. It is the format that Google recommends, that AI crawlers are built to parse, and that consistently performs best for AI visibility. If you are implementing schema markup and not using JSON-LD, you are doing it the hard way.

L

LLM SEO

LLM SEO is a term used to describe search engine optimization strategies specifically targeting large language models. It emphasizes that the "search engines" being optimized for are LLMs like GPT-4, Claude, Gemini, and the models powering Perplexity. LLM SEO is functionally synonymous with GEO and AEO but frames the practice from a more technical perspective.

The term LLM SEO is popular among developers and technical marketers who think about the underlying architecture of AI search. It highlights that these are language models, not traditional search indexes, which helps explain why optimization tactics differ. Content structured for LLM consumption (clear definitions, factual density, explicit answers) performs better than content optimized purely for keyword density and backlinks.

llms.txt

llms.txt is a proposed standard file (placed at the root of a domain, similar to robots.txt) that provides AI models with a structured overview of a website's content, purpose, and key resources. The file gives LLMs context about what the site covers, which pages are most important, and how the content is organized. It is a plain text file designed specifically for machine consumption.

llms.txt is one of the most underutilized GEO tactics available today. Most websites do not have one, which means early adopters gain a structural advantage. By telling AI engines directly what your site is about and which pages contain your best content, you reduce the chance of your site being misunderstood or overlooked. Think of llms.txt as a cover letter for your website, written specifically for AI readers.

M

A magic link, in the context of AI search, refers to a citation link within an AI-generated response that directs users to a specific source. When ChatGPT, Perplexity, or another AI engine includes a hyperlink in its answer pointing to your website, that link functions as a magic link because it carries disproportionate click-through value compared to standard search results. Users trust these links because the AI has effectively pre-vetted and recommended the source.

Magic links are valuable because they represent curated, AI-endorsed traffic. Click-through rates on AI citations tend to be significantly higher than average organic search click-through rates because the user has already received context about why the source is relevant. Earning magic links consistently is the tactical outcome of a successful GEO strategy.

O

OAI-SearchBot

OAI-SearchBot is OpenAI's dedicated search crawler, separate from GPTBot. While GPTBot crawls content for general purposes including model training, OAI-SearchBot specifically crawls content for real-time search results within ChatGPT's search feature. It was introduced as OpenAI expanded ChatGPT's web search capabilities and operates under its own user agent string.

The distinction between GPTBot and OAI-SearchBot matters for robots.txt configuration. Some publishers allow OAI-SearchBot (enabling their content to appear in ChatGPT search results) while blocking GPTBot (preventing their content from being used in model training). If your GEO strategy includes visibility in ChatGPT's real-time search, you need OAI-SearchBot allowed in your robots.txt.

P

PerplexityBot

PerplexityBot is the web crawler operated by Perplexity AI. It crawls and indexes web content to power Perplexity's search engine, which combines LLM capabilities with real-time web retrieval. Perplexity is unique among AI search platforms because every response includes source citations by default, making it one of the most citation-friendly AI engines.

PerplexityBot is a high-priority crawler for GEO because Perplexity's model is built around attribution. When Perplexity answers a query, it always shows its sources. This means that being retrieved and cited by Perplexity is among the most transparent and trackable forms of AI visibility. Perplexity now processes hundreds of millions of queries monthly, and its user base skews toward researchers, professionals, and knowledge workers who are highly engaged.

Q

Query Coverage

Query coverage is the percentage of relevant queries in your topic area for which your content provides a clear, citable answer. If your industry has 100 common questions that people ask AI engines, and your content can answer 60 of them, your query coverage is 60%. Query coverage is a planning metric used to identify content gaps.

High query coverage directly correlates with higher citation rates. The logic is straightforward: you cannot be cited for questions you have not answered. Mapping the full set of queries in your space and systematically creating content that addresses each one is a core GEO content strategy. Start by listing every question your target audience asks AI engines, then audit which ones your existing content already covers.

R

robots.txt (AI Context)

robots.txt is a text file at the root of a website that tells web crawlers which pages they can and cannot access. In the AI context, robots.txt has taken on new importance because it is the primary mechanism for controlling which AI crawlers can access your content. Each AI crawler (GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot, Google-Extended, Bytespider) can be individually allowed or blocked using specific User-agent directives.

Your robots.txt file is the gatekeeper of your AI visibility. If you have not reviewed it with AI crawlers in mind, you should do that today. Many websites are running default configurations that unintentionally block AI crawlers, or they are using overly broad disallow rules that prevent crawling of valuable content. A GEO-optimized robots.txt explicitly allows the AI crawlers you want to reach while managing crawl rates to protect server performance.

S

Schema Markup

Schema markup is a standardized vocabulary of tags (from Schema.org) that you add to your HTML to help search engines and AI systems understand your content. Common schema types relevant to GEO include Article, FAQPage, HowTo, Organization, Person, Product, and Review. Schema markup is typically implemented using JSON-LD format.

Schema markup acts as a translation layer between your content and AI engines. Human readers understand context from visual layout, headings, and reading comprehension. AI crawlers rely heavily on structured data to understand what your content covers and how information is organized. Pages with comprehensive schema markup consistently outperform unstructured pages in AI citation rates because they reduce ambiguity and make extraction easier.

Share of AI Voice

Share of AI voice is a competitive metric that measures how frequently your brand is cited by AI engines compared to your competitors for a defined set of queries. If you track 100 industry queries across ChatGPT, Perplexity, and Gemini, and your brand is cited in 30 of them while your top competitor is cited in 50, your share of AI voice is lower. The metric borrows from the traditional "share of voice" concept in PR and advertising.

Share of AI voice is the competitive intelligence metric for GEO. It tells you not just how you are performing in absolute terms but how you are performing relative to the brands you compete with. Tracking share of AI voice over time reveals whether your GEO strategy is gaining or losing ground. It also identifies which competitors are winning specific query clusters, so you can target those areas with improved content.

V

Visibility Score

A visibility score is a numerical metric that represents a website's overall presence and prominence in AI search results. Visibility scores are calculated by monitoring a set of target queries across multiple AI platforms, tracking citation frequency, citation positioning, and source attribution quality. The score provides a single KPI for GEO performance.

Visibility scores serve the same purpose in GEO that keyword ranking trackers serve in traditional SEO: they give you a number that goes up or down based on your efforts. Without a visibility score, you are stuck with anecdotal evidence and manual spot checks. As the GEO industry matures, visibility scores are becoming the standard way that teams report on AI search performance and justify investment in optimization.

W

Web Search Tool

A web search tool, in the AI context, is a feature built into an AI assistant that allows it to search the live web in real time. ChatGPT's web browsing, Perplexity's search, Claude's web search, and Gemini's grounding all qualify as web search tools. When activated, these tools send crawlers to fetch current web pages, which the AI engine then uses to generate a response with citations.

The web search tool is the mechanism through which most AI citations happen. When an AI engine uses its web search tool, it is actively looking for current, relevant, authoritative content to cite. This is the moment your GEO optimization pays off. Content that is well-structured, recently updated, and directly answering the question being asked is what these web search tools retrieve and present to the user.

How to Use This GEO Glossary

This glossary is designed to be a working reference, not a one-time read. Here are a few ways to get practical value from it.

If you are new to GEO, read through the entries for Generative Engine Optimization, AI Search Visibility, AI Citation, and Content Citability first. Those four terms form the conceptual foundation that everything else builds on.

If you are implementing GEO technically, focus on robots.txt (AI Context), AI Crawlers, GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot, Google-Extended, llms.txt, JSON-LD, Schema Markup, Article Schema, and FAQ Schema. These are the terms that translate into actual configuration changes on your website.

If you are measuring GEO performance, the entries to anchor around are Citation Rate, AI Visibility Score, Share of AI Voice, Visibility Score, and Query Coverage. These define the metrics your team should be tracking.

And if you want a structured approach to tying it all together, look at the CITE Framework entry, which provides a methodology that connects content strategy, technical implementation, and measurement into a single system.

The AI search landscape is changing fast. Terms in this glossary will evolve, and new ones will emerge. We update this reference regularly at GetCited to reflect the latest developments in AI search visibility. If you are building a GEO strategy and want your starting point assessed, GetCited offers AI visibility audits that evaluate your current performance across every dimension covered in this glossary.

Frequently Asked Questions

What is the difference between GEO and AEO?

GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) describe the same core practice: optimizing content so AI-powered platforms cite it in their responses. The term GEO comes from the 2023 Princeton research paper and has broader academic adoption. AEO originated from the featured snippet era and emphasizes the "answer" framing. Use whichever term your team prefers, but know that they refer to the same discipline.

Which AI crawlers should I allow in my robots.txt?

At minimum, most GEO strategies should allow GPTBot (or OAI-SearchBot) for ChatGPT visibility, PerplexityBot for Perplexity visibility, and Google-Extended for Google AI Overviews and Gemini. ClaudeBot is important for Anthropic's Claude. The decision on Bytespider depends on whether you care about ByteDance's AI products. If you are not sure what your current robots.txt allows, run an audit. Many sites block AI crawlers without realizing it.

How do I measure my AI visibility?

AI visibility is measured through citation rate (how often AI engines cite you), share of AI voice (how you compare to competitors), and visibility score (a composite metric across platforms). These require monitoring a defined set of queries across ChatGPT, Perplexity, Gemini, and other AI engines over time. Tools like GetCited automate this tracking, but you can also start manually by querying AI platforms with questions relevant to your industry and documenting whether your brand appears.

Does traditional SEO still matter if I focus on GEO?

Yes. Traditional SEO and GEO are complementary, not mutually exclusive. Strong SEO fundamentals like quality content, good site architecture, and technical health benefit your AI visibility too. AI engines often retrieve content from pages that also rank well in traditional search. The difference is that GEO adds requirements that traditional SEO does not cover, like optimizing for AI crawlers, structuring content for extractability, and maintaining a high content update frequency. The best strategy addresses both.

What is the single most important thing I can do for AI search visibility?

If you can only do one thing, make sure AI crawlers can access your content. Check your robots.txt to confirm that GPTBot, PerplexityBot, ClaudeBot, and Google-Extended are not blocked. No amount of content optimization matters if AI engines literally cannot reach your pages. After that, the highest-impact action is structuring your content to lead with direct, clear answers to the questions your audience asks. AI engines are looking for content that answers questions authoritatively. Give them exactly that.