The AI Search Glossary for Businesses: AEO, GEO, RAG, LLM and More Explained
Updated: Sep 3
Why This Glossary Exists
These terms exist because the underlying platforms have grown fast — AI tools jumped from 6% to 45% usage for local recommendations in a single year, per BrightLocal’s 2026 survey, and AI Overviews now appear on roughly 48% of all Google queries.
AI search brought a wave of new terminology into digital marketing conversations almost overnight — AEO, GEO, RAG, LLM, and dozens more acronyms and concepts that didn't exist in mainstream marketing vocabulary even a few years ago. If you've felt lost in a conversation with a marketer or read an industry article and hit a wall of unfamiliar jargon, this glossary is meant to fix that, in plain English, without the circular definitions that make so many of these explainers useless.
Core Concepts
AEO (Answer Engine Optimization). The practice of structuring content so it can be directly extracted and presented as a complete answer by AI systems — featured snippets, AI Overviews, voice assistants — rather than just ranked as a link a user has to click to get the answer themselves.
GEO (Generative Engine Optimization). The practice of building the trust, credibility, and verifiable digital presence that makes generative AI systems (ChatGPT, Gemini, AI Overviews) confident enough to cite your business as a source when generating an answer. Where AEO is mostly about content format, GEO is mostly about earned trust.
LLM (Large Language Model). The type of AI model — like GPT, Gemini, or Claude — trained on massive amounts of text to understand and generate human-like language. This is the underlying technology powering ChatGPT, AI Overviews, and most modern AI search and chat tools.
RAG (Retrieval-Augmented Generation). A technique where an AI system retrieves current, relevant information from an external source (like a live web search) before generating its answer, rather than relying solely on what it learned during training. This is how AI Overviews and browsing-enabled ChatGPT stay current instead of only knowing what was true as of their training cutoff.
Search and Discovery Terms
Zero-Click Search. A search where the user's need is fully met by information shown directly on the results page — a featured snippet, AI Overview, or knowledge panel — without them clicking through to any website.
AI Overview. Google's AI-generated summary that appears at the top of search results for many queries, synthesized from multiple sources and shown above traditional ranked links.
AI Mode. Google's more conversational, chat-based search experience, allowing multi-turn, follow-up-capable interaction rather than a single query-and-results-page exchange.
SGE (Search Generative Experience). The original name for what became AI Overviews — Google's experimental, Labs-only precursor launched in 2023 before the feature rolled out broadly.
Featured Snippet / Position Zero. A single highlighted result, sourced from one webpage, shown above the traditional ranked results, directly answering the searcher's query.
Knowledge Graph. Google's structured database of real-world entities — people, places, businesses, concepts — and the verified relationships between them, used to power Knowledge Panels and inform AI-generated answers.
Knowledge Panel. The information box, typically on the right side of Google search results, showing key facts about a recognized entity like a business, person, or place.
Trust and Credibility Terms
E-E-A-T (Experience, Expertise, Authoritativeness, Trust). Google's framework, from its Search Quality Rater Guidelines, for evaluating the credibility of content and its source — now applied algorithmically by AI systems deciding what to cite, not just by human quality raters.
Entity SEO. The practice of establishing your business as a clearly identified, verified "entity" — with consistent, corroborated data across multiple sources — that search engines and AI systems can confidently recognize and trust, independent of any single page's keyword optimization.
NAP Consistency. Ensuring your business Name, Address, and Phone number appear identically across your website, Google Business Profile, and every directory listing — a foundational trust and entity-verification signal.
Schema Markup / Structured Data. Standardized, machine-readable code added to a webpage (in JSON-LD format) that explicitly tells search engines and AI crawlers what the content is — a business, an article, a set of FAQs — rather than leaving them to infer it.
Citation (in an AI context). A source an AI system references, and often links to, when generating an answer — functionally similar to a footnote, and one of the clearest markers that your content has been trusted enough to inform an AI-generated response.
More Terms Worth Knowing
YMYL (Your Money or Your Life). Google's classification for content categories — health, finance, safety, legal — where inaccurate information carries genuine potential for real-world harm, and where both traditional ranking and AI systems apply stricter quality and trust standards before surfacing a source.
Hallucination. When an AI system generates information that sounds plausible and confident but is factually incorrect or fabricated, not drawn from real, verified data. This is one of the core reasons trust and verification signals (GEO, E-E-A-T) matter so much to AI system design.
Agentic AI / Agentic Search. AI systems capable of taking multi-step action on a user's behalf — not just answering a question, but comparing options, checking availability, or initiating a task like a booking — rather than simply generating a response.
Multimodal Search. Search that accepts more than typed text as input — a photo, a voice query, a live video feed — and can combine multiple input types within a single interaction.
Prompt. The input a user gives an AI system — a question, instruction, or request — that the system responds to. In an AI search context, a prompt functions similarly to a traditional search query, though often phrased more conversationally.
Training Data / Training Cutoff. The body of text an AI model learned from, and the date after which it has no built-in knowledge unless supplemented by retrieval (RAG) or live browsing. This is why browsing-enabled AI answers can reflect current information while a model's un-augmented "memory" cannot.
A Few More Terms You'll Increasingly Run Into
Vector Embedding. A numerical representation of the meaning of a word, phrase, or document that lets AI systems compare concepts by similarity of meaning rather than exact keyword matching. This is the underlying mechanism behind semantic search — it's why a query about "affordable family dentist" can match content that never uses those exact words, as long as the underlying concepts are close enough in meaning.
Passage Indexing. Google's ability to rank and retrieve a specific, relevant passage within a longer page, rather than only evaluating the page as a whole. This is part of why a single comprehensive page covering many subtopics can still surface for a very specific query — the system identifies and retrieves the one relevant passage, not just the page's overall theme.
Freshness Signal. A general term for evidence that content is current and actively maintained — a visible last-updated date, recent citations, current pricing or availability information. AI systems weigh freshness more heavily for time-sensitive topics like pricing, availability, and medical guidance than for genuinely evergreen ones.
Frequently Asked Questions
What's the simplest way to explain the difference between AEO and GEO?
AEO is about how your content is formatted so an AI system can pull a direct answer from it — clear headings, direct answers, FAQ structure. GEO is about whether the AI system trusts your business enough to cite it at all — earned through consistent, verifiable entity signals, schema markup, and credibility. Put simply: AEO gets you extractable, GEO gets you trusted, and a strong AI search strategy needs both working together, not just one or the other.
Is "SEO" still a relevant term, or has it been replaced by AEO and GEO?
SEO is still very relevant — it's the foundation everything else builds on. A page with no traditional SEO fundamentals in place (technical health, relevant content, basic authority) generally won't get retrieved as candidate material for AI Overviews or chat assistant answers in the first place. AEO and GEO are additional, complementary layers addressing how AI systems specifically consume, extract, and trust content, not replacements for the search engine optimization fundamentals that came before them.
What does it mean when someone says an AI system "hallucinates"?
Hallucination refers to an AI system generating information that sounds plausible and confident but is factually incorrect or fabricated — not sourced from real, verified data. It happens because language models generate the most statistically likely next words, which usually produces accurate text but occasionally produces confident-sounding fiction. This is part of why trust and verification signals matter so much: they give AI systems real, checkable data to ground answers in.
Do I need to understand all of these terms to do AI search optimization for my business?
No — understanding the core concepts (AEO, GEO, zero-click search, entity SEO, schema markup) covers most practical decision-making a business owner needs to make. The more technical terms, like RAG and vector embeddings, are useful context for understanding how these systems work under the hood, but they're not essential for day-to-day optimization decisions, which come down to a fairly short, practical list: be accurate, be consistent, be structured, and be verifiable.
Will this glossary need to be updated as AI search continues to evolve?
Almost certainly — this is a fast-moving area, and new terminology emerges as platforms add capabilities and new AI search products launch. The core concepts here — answer extraction, trust and verification, entity recognition, semantic matching — are likely to remain foundational even as the specific tools and terms surrounding them continue to shift, the way "SGE" gave way to "AI Overviews" without the underlying concept changing much.
Do these terms mean the same thing across every AI platform, or does terminology vary?
The underlying concepts are broadly consistent, but the exact terminology and branding vary by platform — what Google calls an "AI Overview," other companies describe with their own product names, and technical terms like RAG or embeddings are used fairly consistently across the industry regardless of which specific AI product is being discussed. When in doubt, it's usually more useful to understand the underlying mechanism a term describes than to memorize platform-specific branding, since the mechanisms tend to be shared even when the names aren't.
Is there a specific term for when an AI answer references a business but doesn't link to it?
This is often called an unlinked citation or unlinked mention, and it's an increasingly important concept in GEO — an AI system can reference or describe your business by name in a generated answer without including a clickable source link, which means your brand is influencing the response without generating a trackable visit. This is one reason brand visibility in AI answers needs to be measured differently than clicks alone; the influence can be real even when the traffic isn't.
Related Reading
Still Have Questions About Where Your Business Fits Into All This?
Terminology aside, the practical question for most businesses is simple: is your website actually set up to be found, extracted, and trusted by the AI systems your customers are already using? Do It With You Marketing translates all of this jargon into a concrete, prioritized plan for your specific business.
If you'd like help sorting out what actually matters for your site, call our Decatur, AL team at (256) 274-1289 or email info@diwym.com and we'll walk you through it in plain English.