The AI SEO Glossary: GEO, AEO & AI Search Terms Defined

AI SEO

AI SEO is the practice of optimizing a website to be found, understood, and cited across AI-driven search — Google AI Overviews, ChatGPT, Gemini, Perplexity, and Copilot — in addition to traditional Google rankings. It combines classic SEO fundamentals (crawlability, relevance, links) with structured data, entity clarity, and answer-first content that language models can quote directly. The goal is visibility wherever people now research, not just on the ten blue links.

GEO (generative engine optimization)

Generative engine optimization is the practice of structuring content so generative AI engines retrieve it, trust it, and cite it inside their synthesized answers. The term was introduced in a 2023 academic paper, and the discipline emphasizes quotable statistics, clean passage structure, outbound citations, and entity signals over classic ranking tactics. GEO measures success by citations and inclusion in AI answers, not by position alone. See generative engine optimization services for the applied version.

AEO (answer engine optimization)

Answer engine optimization is the practice of structuring content so answer engines can extract a single, direct response to a specific question. Answer engines include Google's featured snippets and AI Overviews, voice assistants, and chat interfaces like ChatGPT. AEO prioritizes concise self-contained answers placed directly under question-style headings, FAQ markup, and factual precision. Learn more in answer engine optimization services.

LLM SEO

LLM SEO is optimizing content specifically for large language models — the systems behind ChatGPT, Claude, and Gemini — so they recognize a brand and reference it in responses. It overlaps heavily with GEO and AEO, but frames the target as the model itself: its training impression of your brand and its live retrieval of your pages. See LLM SEO services for detail.

Search everywhere optimization

Search everywhere optimization is the strategy of being discoverable across every surface where people now search — Google, AI engines, YouTube, Amazon, TikTok, Reddit, maps, and app stores — rather than treating Google web search as the only channel. It reflects the reality that a single buyer research journey now spans many search-like tools. See search everywhere optimization.

AI Overviews

AI Overviews are Google's AI-generated summaries that appear at the top of some search results, powered by its Gemini models. They synthesize an answer from multiple web pages and display links to the cited sources. Rolled out broadly in the US in 2024, they often satisfy the query on the page itself, changing how much traffic reaches individual sites. See how AI Overviews work.

AI Mode

AI Mode is Google's dedicated conversational search experience, offered as a separate mode, that handles complex, multi-part questions with a fuller generative response than a standard AI Overview. It uses query fan-out to research several angles of a question at once and supports follow-up questions in a chat-style thread. It expanded in the US through 2025.

Query fan-out

Query fan-out is the technique Google's AI search uses to break a single question into multiple related sub-queries, run them in parallel, and synthesize the results into one answer. The practical consequence is that a page can be pulled into an answer for being relevant to a sub-question the user never explicitly typed. Covering a topic's real sub-questions — not just the headline keyword — is how you get surfaced.

RAG (retrieval-augmented generation)

Retrieval-augmented generation is the architecture that lets a frozen language model answer with live information. Instead of relying on memory alone, the engine retrieves relevant web documents at answer time, loads their passages into its context, and generates a response grounded in them with citations. Every consumer AI search product — ChatGPT search, Perplexity, Gemini — is a RAG system. See how generative engines work.

Grounding

Grounding is the constraint that ties an AI's answer to retrieved source documents rather than to the model's unverified memory. A grounded engine builds its response from the passages it just read and attaches citations to specific claims. When grounding fails — when a model answers from memory alone — it is most likely to invent a detail.

Vector embedding

A vector embedding is a list of numbers that represents the meaning of a piece of text, so an engine can compare ideas mathematically. Passages about the same concept land near each other in that space even when they share no exact words, which is why retrieval matches meaning rather than literal keywords. Plain, specific writing embeds cleanly; vague marketing copy embeds into a fuzzy region that matches nothing.

Citation

In AI search, a citation is the source link an engine attaches to a claim in its answer, crediting the page whose content supported that statement. Citations are earned through crawler access, quotable facts, and entity clarity — not bought — and the credited page is often a mid-sized site rather than the biggest brand. Ranking no longer guarantees the citation: Ahrefs found the share of AI Overview citations drawn from Google's top-10 organic results fell from 76% to 38% in a single year.

Answer-first content

Answer-first content is a writing structure that leads with the direct, self-contained answer to the query before any background or marketing copy. It serves both humans skimming for a fast answer and AI engines that lift a single passage to ground a response. In practice it means a 40-60 word answer immediately under a question-style heading.

Semantic completeness

Semantic completeness is how fully a page answers a query along with the related sub-questions a reader actually has. Engines favor complete coverage because a page that resolves the whole question — definitions, comparisons, caveats, and next steps — gives grounding more to work with. It is depth measured by usefulness, not by word count.

Hallucination

A hallucination is a fluent, confident statement generated by an AI that is not true. It is a structural feature of how language models predict plausible text — plausible is not the same as verified. Grounding, corroboration filtering, and recency weighting are the main guardrails engines use to reduce it.

Zero-click search

A zero-click search is a search that ends without the user clicking through to any website, because the answer appears directly on the results page — via a featured snippet, AI Overview, knowledge panel, or map pack. Zero-click results have grown as AI answers expand, which raises the value of being the cited source inside the answer rather than the tenth blue link below it.

Entity

An entity is a distinct, uniquely identifiable thing — a person, place, organization, product, or concept — that a search engine recognizes and can connect to other things. Modern search has shifted from matching keyword strings to understanding entities and the relationships between them. Being a clearly-defined entity is what lets an engine confidently name your business in an answer. See how entity SEO works.

Entity optimization

Entity optimization is the work of making a brand a clearly-defined, well-corroborated entity across the web so engines can identify it without ambiguity. It includes consistent naming, structured data, a stable knowledge-graph identity, and third-party mentions that agree with each other. It is the infrastructure beneath AI citation, because an engine cannot credit a business it cannot confidently resolve. See how entity SEO works.

Knowledge graph

A knowledge graph is a structured database of entities and the relationships between them, used to disambiguate meaning and power features like Google's knowledge panels. When your business exists cleanly in the graph, engines know which "Acme" you are and what you do. Consistent data and authoritative references are what write a brand into it.

sameAs

sameAs is a schema.org property that links an entity on your site to its authoritative profiles elsewhere — LinkedIn, Wikipedia, Wikidata, official social accounts, or industry directories. It corroborates identity by tying your one entity to the wider web's record of it. A person or organization node with no sameAs is an unverified assertion that engines weight lightly.

Topical authority

Topical authority is the depth and breadth of a site's coverage across a subject, which signals genuine expertise rather than a single opportunistic page. A site that answers the full spectrum of questions in its niche — thoroughly and accurately — earns more trust from both rankers and AI engines. It is built by covering a topic completely and interlinking the pieces, not by chasing one keyword.

GPTBot

GPTBot is OpenAI's web crawler that collects publicly available data used to help train its models. It identifies itself with the user agent GPTBot and respects robots.txt directives, so publishers can allow or block it. Blocking GPTBot limits your content's presence in future training data but is separate from ChatGPT's live search.

OAI-SearchBot

OAI-SearchBot is OpenAI's crawler that discovers and indexes sites so they can be surfaced and linked as sources in ChatGPT search results. Per OpenAI, it is used for search discovery, not for training models. Blocking it can remove a site from ChatGPT's cited results, which is often the opposite of what a business wants.

ChatGPT-User

ChatGPT-User is the user-triggered agent OpenAI uses to fetch a specific page live when a ChatGPT user's request requires browsing. Because these fetches are initiated by a real user action rather than bulk crawling, allowing this agent keeps your pages reachable when someone asks ChatGPT about your business directly.

PerplexityBot

PerplexityBot is Perplexity AI's crawler that indexes web pages so they can be retrieved and cited in Perplexity's answers. Allowing it is a prerequisite for appearing as a source in Perplexity, an engine built around visible citations. It is declared in robots.txt like any other crawler.

ClaudeBot

ClaudeBot is Anthropic's web crawler that gathers publicly available data used to train the Claude family of models, and it respects robots.txt. Anthropic also operates separate agents for search and user-initiated fetches, so a business can make distinct choices about training versus live retrieval. Its presence in your logs indicates Anthropic has crawled your pages.

Google-Extended

Google-Extended is a robots.txt product token — not a separate crawler with its own user agent — that lets publishers control whether their content is used to train Google's Gemini and Vertex AI generative models. Disallowing Google-Extended does not affect how a site is crawled, indexed, or ranked in Google Search. It is purely an AI-training opt-out.

Applebot-Extended

Applebot-Extended is Apple's robots.txt control that lets publishers opt out of having their content used to train Apple's generative AI models. It is distinct from Applebot, the crawler that powers Siri and Spotlight suggestions; blocking the training token does not remove a site from those features. Like Google-Extended, it is a training-use control rather than a crawler.

Bingbot

Bingbot is Microsoft's web crawler that builds the Bing search index. Because Microsoft Copilot draws on that index for retrieval, Bingbot access influences visibility in both Bing search and Copilot's AI answers. Keeping it unblocked matters more than many businesses realize, given Copilot's reach in Windows and Edge.

llms.txt

llms.txt is a proposed plain-text file, placed at a site's root (/llms.txt), that offers language models a curated, Markdown-formatted map of a site's most important content. It is an emerging community convention, not an official standard, and major AI companies have not confirmed that their systems read it as of 2026. Treat it as low-cost, forward-looking housekeeping rather than a proven ranking factor — details in what is llms.txt.

robots.txt

robots.txt is a plain-text file at a site's root that tells compliant crawlers which paths they may or may not access. It is the primary place to allow or disallow specific AI and search bots by user agent. It is a request that well-behaved crawlers honor, not an enforced security control.

Crawl budget

Crawl budget is the number of pages a search engine will crawl on a site within a given period, shaped by the site's size, speed, and perceived importance. It mainly matters for large sites, where wasted crawling on low-value or duplicate URLs can delay the discovery of pages that matter. Clean architecture, fast responses, and good internal linking spend it efficiently.

Schema.org / structured data / JSON-LD

Structured data is machine-readable code that labels the meaning of content on a page — marking what is a product, a review, an FAQ, or an organization. Schema.org is the shared vocabulary that defines those types, and JSON-LD is the Google-recommended format for adding it, placed in a script tag in the page's HTML. It helps engines understand and confidently reuse your content, and can enable rich results. See how schema markup works.

FAQPage

FAQPage is a schema.org type that marks up a list of questions and their answers so engines can recognize them as a structured Q&A. Correctly implemented on genuine question-and-answer content, it clarifies the page's meaning for both search and AI systems. It should only wrap real FAQs that are visible on the page, per Google's guidelines.

E-E-A-T

E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness — the framework Google's quality raters use to assess content and its creators. It is not a direct ranking score but a set of signals, such as a credentialed author, cited sources, and a verifiable reputation, that correlate strongly with both rankings and AI citations. Trust is the component Google describes as most important. See how E-E-A-T works.

Featured snippet

A featured snippet is a short answer Google extracts from a web page and displays in a highlighted box at the top of some results, with a link to the source. It is a long-standing form of answer-first result and a common precursor to being pulled into an AI Overview. Winning one rewards concise, directly-structured answers to a specific question.

People Also Ask (PAA)

People Also Ask is the expandable list of related questions Google shows within results, each revealing a snippet answer sourced from a web page. PAA reveals the real sub-questions searchers have around a topic, which makes it a practical map for answer-first content and FAQ sections. Covering these questions well supports both snippet capture and AI answer inclusion.

Canonical

A canonical tag (rel="canonical") tells search engines which URL is the preferred, authoritative version when similar or duplicate content exists at multiple addresses. It consolidates ranking signals onto one URL and prevents duplicates from competing with each other. Correct canonicalization keeps an entity's pages pointing to a single, clear identity.

SERP

SERP stands for Search Engine Results Page — the page a search engine returns for a query. Modern SERPs mix organic listings with AI Overviews, featured snippets, People Also Ask, map packs, ads, and knowledge panels. Understanding a query's SERP layout reveals what format an engine rewards for that intent.

Map pack

The map pack (or local pack) is the block of typically three local business listings shown with a map at the top of Google's results for location-based queries. Appearing in it is the highest-visibility position in local search and is driven by proximity, relevance, and prominence. It is a frequent zero-click surface, since users often call or get directions without visiting a website.

NAP

NAP stands for Name, Address, and Phone number — the core identity details of a local business. Keeping NAP identical everywhere it appears, from your site to directories to your Google Business Profile, is fundamental to local SEO and entity resolution. Inconsistent NAP data confuses engines about which business is which and can suppress local visibility.

GBP (Google Business Profile)

Google Business Profile (formerly Google My Business) is the free listing a business manages to control how it appears in Google Search and Maps, including hours, photos, reviews, and services. A complete, accurate, actively-managed profile is the single most influential asset in local and map-pack visibility. See Google Business Profile optimization.

Local citations

Local citations are online mentions of a business's name, address, and phone number on directories, review sites, and industry platforms. Consistent citations across trusted sources corroborate a business's existence and details, strengthening both local rankings and entity confidence. They are a core part of local SEO services.

CTR (click-through rate)

Click-through rate is the percentage of people who click a listing after seeing it, calculated as clicks divided by impressions. In search, CTR reflects how compelling a title and meta description are at a given position. As AI Overviews and zero-click results absorb more answers, organic CTR for informational queries has come under pressure, shifting the value toward being the cited source.

AI visibility

AI visibility is a measure of how often, how accurately, and how prominently a brand appears in AI-generated answers across engines like ChatGPT, Gemini, Perplexity, and Google AI Overviews. Because there is no single dashboard for it, it is tracked by testing a fixed basket of real queries across engines and recording mentions, sentiment, and citations over time. It is the AI-era counterpart to keyword rankings.

Share of voice (AI)

AI share of voice is the proportion of AI answers in a given topic or market that mention or cite your brand versus competitors. It reframes visibility as a competitive percentage rather than an absolute count, which makes progress legible month over month. Like AI visibility, it is measured against a fixed, repeatable query set to avoid distortion.

A note on method: these definitions are the ones AISEO USA uses in its own work, written for accuracy over hype. Where a mechanic of a real product is described (crawler behavior, AI Mode, Google-Extended), it reflects the vendors' published documentation — not guesswork. The discipline these terms describe is influenceable but not guaranteed: a peer-reviewed study found that optimizing content for generative engines lifted source visibility by up to 40%, yet no one can promise a specific citation, because the systems are probabilistic by design.