What This Glossary Is

    This glossary defines the core terms used in AI-driven search, optimization, and answer engines. It is designed for marketers, SEOs, founders, and technical teams who need precise, modern definitions aligned with how search actually works in 2025 and beyond.

    Unlike traditional SEO glossaries, these definitions reflect:

    • AI Overviews
    • Answer engines
    • Entity-based retrieval
    • LLM citation behavior
    • Zero-click and synthesis-first search

    AI SEO Terms & Definitions

    AI SEO

    AI SEO is the practice of optimizing content, entities, and digital signals so they can be retrieved, understood, and cited by AI-driven search systems, including large language models and search engines that generate synthesized answers.

    AI SEO goes beyond ranking web pages and focuses on inclusion, attribution, and authority inside AI outputs.

    AI Engine Optimization (AEO)

    AI Engine Optimization (AEO) is a subset of AI SEO focused specifically on optimizing content so it can be used as a direct answer source by AI engines such as Google AI Overviews, ChatGPT, and Perplexity.

    AEO prioritizes:

    • Clear answer blocks
    • Entity clarity
    • Structured facts
    • Citation-ready formatting

    Answer Engine

    An answer engine is a system that generates direct responses to user questions instead of returning a list of links.

    Examples include AI-powered search interfaces and conversational AI tools. These systems rely on retrieval + synthesis, not traditional ranking alone.

    AI Overview

    An AI Overview is a machine-generated summary displayed at the top of search results that synthesizes information from multiple sources.

    Content included in AI Overviews is selected, not ranked, making entity authority and clarity critical.

    Entity

    An entity is a uniquely identifiable person, business, place, concept, or thing that AI systems can recognize, store, and reference.

    In AI SEO, entities act as primary nodes that AI engines use to understand relationships, credibility, and topical authority.

    Entity SEO

    Entity SEO is the process of structuring content and data so AI systems clearly understand:

    • Who you are
    • What you do
    • Where you operate
    • How you are connected to related topics and entities

    Entity SEO reduces ambiguity and increases retrieval probability.

    Retrieval

    Retrieval is the process by which AI systems select sources before generating an answer.

    Unlike traditional ranking, retrieval focuses on:

    • Relevance
    • Entity confidence
    • Topical coverage
    • Trust signals

    If content is not retrieved, it cannot be cited.

    Synthesis

    Synthesis is the process where an AI engine combines information from multiple retrieved sources into a single response.

    Optimized content is written so its facts and phrasing can be easily merged without distortion.

    Zero-Click Search

    Zero-click search occurs when a user receives an answer directly from the search interface without clicking a website.

    AI SEO embraces zero-click visibility by optimizing for citations, mentions, and authority, not just traffic.

    AI Citation

    An AI citation is when an AI engine references or links to a source while generating an answer.

    Citations are a primary success metric in AI SEO because they signal trust and influence future retrieval.

    Knowledge Graph

    A knowledge graph is a structured network of entities and their relationships used by search engines and AI systems to understand the world.

    AI SEO aligns content to reinforce and expand how an entity appears within these graphs.

    Semantic Search

    Semantic search focuses on meaning, context, and intent rather than exact keyword matching.

    AI SEO relies heavily on semantic optimization to ensure content aligns with how AI interprets language and concepts.

    Topical Authority

    Topical authority is the level of trust an AI system assigns to a source for a specific subject area.

    It is built through:

    • Comprehensive coverage
    • Consistent entity signals
    • Accurate, repeatable answers
    • External validation

    LLM (Large Language Model)

    A large language model (LLM) is an AI system trained on vast datasets to understand and generate human language.

    Search engines increasingly use LLMs to interpret queries, retrieve sources, and generate responses.

    Structured Data

    Structured data is machine-readable markup that helps search engines and AI systems understand content structure, facts, and relationships.

    In AI SEO, structured data supports clarity but does not replace strong entity alignment.

    GEO (Generative Engine Optimization)

    Generative Engine Optimization (GEO) is the broader strategy of optimizing content to influence generative outputs, not just search rankings.

    AI SEO and AEO are practical implementations of GEO.