ProCited AI Visibility Glossary | AIVO, GEO, AEO & AI SEO

How to use this glossary

Some terms below are established technical, search, marketing or AI-industry terms. Others are ProCited working terms or phrases used within The Echo Principle™ and the ProCited AIVO Method. Where terminology is emerging or not universally standardised, the definition explains how ProCited uses it rather than presenting one interpretation as universally accepted.

Last updated: 15 August 2026 — a living glossary reviewed as AI terminology evolves.

How this differs from The Echo Principle glossary

The Echo Principle glossary stays focused on Voice, Echoes, entity corroboration, recognition, confidence and recommendation. This ProCited glossary is intentionally broader. It also covers ProCited’s consultancy services, AIVO, GEO, AEO, AI SEO, AI search, AI Visibility measurement, wider AI-search terminology and the emerging agentic layer in which AI systems may discover, evaluate, select and transact with people, businesses, brands, products and services.

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A

Agent Interoperability

Agent Interoperability is the ability of AI agents created by different companies, platforms or technical frameworks to discover one another, communicate and collaborate.

It matters because a customer’s agent may need to work with merchant, supplier, booking, payment and delivery systems that were not built by the same provider.

Agent-Ready Business

ProCited working term

An Agent-Ready Business is a business whose identity, products, services, availability, pricing, policies, locations and transaction processes are sufficiently clear and accessible for authorised AI agents to discover, evaluate and interact with.

Agent readiness may involve webpages, structured data, product feeds, APIs, commerce protocols, tool connections and suitable payment or fulfilment systems. The exact requirements depend on the business and the actions an agent is expected to perform.

Agent-to-Agent Interaction

Agent-to-Agent Interaction occurs when one AI agent communicates, delegates or coordinates with another AI agent to complete a task.

This is more precise than saying that chatbots talk to chatbots because the systems may exchange structured information, capabilities and task status without using a human-style conversation.

Agent2Agent Protocol (A2A)

Named protocol

The Agent2Agent Protocol (A2A) is an open standard that allows AI agents built by different organisations, vendors or technical frameworks to discover one another, exchange information and coordinate work.

A2A is primarily concerned with agent-to-agent communication. It complements protocols such as MCP, which connect AI applications and agents to tools, data and external systems.

Agentic AI

Agentic AI is artificial intelligence designed to pursue goals and complete multi-step tasks with a degree of autonomy. It may plan, use tools, respond to changing information and decide which authorised action to take next.

Agentic AI is the broader technology category. Agentic commerce, shopping agents and agentic payments are applications of it.

Agentic Commerce

Agentic Commerce is commerce in which an AI agent helps perform or completes parts of the buying process on behalf of a person or business.

This may include researching options, comparing products or suppliers, checking availability, selecting an offer, arranging payment, coordinating delivery and managing later actions within permissions, spending limits or approval rules set by the user.

Agentic Commerce Protocol (ACP)

Named protocol

The Agentic Commerce Protocol (ACP) is an open standard for connecting AI-led shopping experiences with merchant product information and commerce systems.

It can support structured product discovery and transaction flows while allowing the merchant to retain responsibility for orders, fulfilment, returns, support and the customer relationship. Because ACP is a named technical protocol, its capabilities and specification may evolve.

Agentic Payment

An Agentic Payment is a payment initiated or completed by an authorised AI agent on behalf of a person or business.

Agentic payments may use identity checks, spending limits, approval requirements, payment credentials and transaction records to establish what the agent is permitted to buy and to verify the user’s authority.

Agentic Visibility

ProCited working term

Agentic Visibility is the ability of a business, product, service or other entity to be discovered, understood, evaluated and selected by AI agents acting on behalf of people or organisations.

AI Visibility asks whether an entity can become part of an AI-generated conversation. Agentic Visibility goes further by asking whether an agent can obtain enough reliable, current and actionable information to consider the entity and take an authorised next step.

AI Agent

An AI Agent is an artificial intelligence system that can interpret a goal, plan steps, access information, use tools and take authorised actions on behalf of a person, organisation or another system.

Unlike an assistant that only returns an answer, an agent may continue by searching, comparing, booking, ordering, updating records or completing another permitted task.

AI Assistant

An AI Assistant is a user-facing application that allows people to interact with artificial intelligence through natural-language questions and instructions.

An assistant may produce answers, use tools or include agentic capabilities. The application people interact with is not necessarily the same thing as the underlying language model.

AI Citation

An AI Citation is a visible link or reference from an AI-generated answer to a webpage, document or other source.

The citation identifies a source supporting part of the answer. This is different from an AI Mention, which means the business, brand or other entity is named within the generated answer.

A source can be cited without its associated brand being mentioned. This is sometimes described as a Ghost Citation.

AI Citation Rate

AI Visibility metric

AI Citation Rate is the percentage of tested AI-generated answers that visibly cite or link to a specified website, webpage, source or domain.

The metric is also commonly shortened to Citation Rate in AI Visibility reporting.

It is calculated by comparing the number of answers containing the specified citation with the total number of relevant answers included in the assessment.

An AI Citation Rate is meaningful only when the testing scope is clearly stated, including the AI platforms, prompts, dates, locations, number of tests and criteria used to count a citation.

Citation Rate does not measure whether the associated brand was mentioned, whether the information was represented accurately or whether the entity was recommended.

AI Confidence

ProCited practical term

AI Confidence is a practical way of describing reduced uncertainty in an AI system’s understanding of an entity.

It does not mean that AI trusts a business as a person would. It means the available information forms a clearer, more consistent and better-corroborated pattern.

AI Conversation Strategy

ProCited service

AI Conversation Strategy is the ProCited service that identifies the questions, comparisons, explanations and recommendations an entity should reasonably become part of — and the answers and evidence needed to support that position.

It connects what the person, business, brand, product or service wants to be known for with the questions its audience asks before choosing, comparing or recommending an option.

The Strategy identifies the strongest supportable answers, the information that should appear on first-party sources and the evidence that should be reinforced across credible third-party sources.

Explore AI Conversation Strategy

AI Crawlability

ProCited practical term

AI Crawlability is the degree to which authorised search-engine and AI-related crawlers can access and process the pages, files and resources on a website.

It may be affected by robots directives, server responses, authentication, paywalls, rendering requirements, blocked resources, technical errors and the structure of the website.

A page can be crawlable without being selected, retrieved, cited or used in an AI-generated answer. Crawlability creates access; it does not guarantee visibility.

Within ProCited’s methodology, AI Crawlability is part of the technical foundation supporting On-Site AI Visibility.

AI discovery

AI discovery is the process through which people find, compare or learn about businesses, products, services, professionals or places through AI assistants and AI-enhanced search experiences.

AI Invisibility

ProCited practical term

AI Invisibility is the condition in which a business, brand, product, service, person or other entity is absent from relevant AI-generated answers, comparisons, citations or recommendations.

It may result from weak entity clarity, insufficient digital evidence, conflicting information, limited off-site corroboration or an absence of relevant signals.

AI Mention

An AI Mention occurs when the name of a business, brand, person, product, service or other entity appears within an AI-generated answer.

A mention may appear with a supporting AI Citation or without any visible citation or link.

AI Mode

Named Google feature

AI Mode is a Google Search experience that uses generative AI to produce responses to complex questions and support follow-up exploration.

It may carry out multiple related searches, gather information from different sources and synthesise that information into a generated response with supporting links.

For ProCited, AI Mode is one AI-search surface where a business, person, product, service or other entity may be discovered, mentioned, cited, compared or recommended.

Visibility in AI Mode does not guarantee a citation, recommendation or website visit.

AI Noise

ProCited usage

ProCited uses AI Noise to describe content, mentions, signals or online activity that create apparent volume without meaningfully strengthening AI understanding, representation or visibility.

AI Noise can include repetitive low-value content, disconnected mentions, duplicated claims, irrelevant placements or large quantities of information that do not improve entity clarity or credible corroboration.

The phrase AI Noise is used more broadly in technology and marketing, but this is the specific meaning ProCited uses within its AI Visibility methodology.

Not every mention is an Echo. Some are just AI Noise.

AI Optimisation (AIO)

AI Optimisation (AIO) is a broad umbrella term for work intended to improve how content, organisations and other entities are discovered, interpreted or represented by AI systems.

The label is not used consistently across the industry. ProCited uses AIVO when the specific objective is AI Visibility and AEO when the focus is direct answers. The full phrase should be used when precision matters because AIO is also used informally for AI Overviews.

AI Overview

An AI Overview is a Google Search feature that uses generative AI to provide a summarised response for some searches and may display supporting links.

For ProCited, AI Overviews are one AI-search surface where a business may be mentioned, described, cited or linked. Not every search produces an AI Overview, and appearing does not guarantee a website visit.

AI search

AI search is the broader search and discovery environment in which AI systems interpret questions and generate or synthesise answers, summaries, comparisons and recommendations rather than presenting only a conventional list of links.

AI search can combine information from multiple sources and present a generated response directly to the user.

For AI Visibility, this changes the opportunity from simply having a webpage that can be found to also providing clear, relevant and credible information that can help a person, business, brand, product or service become part of the generated answer.

AI SEO

Informal and increasingly common industry term

AI SEO is the application and evolution of search optimisation for an AI-driven search environment.

The term is used in more than one way across the industry. It can refer to using artificial intelligence to perform or support traditional SEO work, but it is also increasingly used to describe adapting websites, content and entity information for AI-driven search experiences that generate synthesised answers.

At ProCited, AI SEO refers to applying important SEO foundations — including technical accessibility, discoverability, content quality, relevance and clear site structure — within an AI search environment where systems also need to recognise entities, retrieve information, understand relationships and generate answers.

ProCited treats AI SEO as one of the disciplines contributing to the broader AI Visibility Optimisation (AIVO) approach.

AI SEO is not a sixth ProCited service.

Because the phrase can also mean AI-assisted SEO, its intended meaning should be made clear when it is used.

AI Shopping Agent

An AI Shopping Agent is an AI agent specialised in discovering, comparing, selecting and potentially purchasing products or services on behalf of a customer.

It may consider price, quality, availability, location, delivery time, dietary or accessibility needs, previous preferences, loyalty benefits and an authorised spending limit.

AI Source

An AI Source is a webpage, document, profile, dataset, publication or other information source that an AI system retrieves, uses or displays when producing an AI-generated answer.

An AI source may contribute information to an answer without being visibly identified. When the source is visibly linked or referenced within the answer, that visible reference becomes an AI Citation.

A source displayed within a Google AI Overview is one example of an AI source.

AI Visibility

AI Visibility is the ability of a person, business, brand, product, service or other entity to be discovered, recognised, understood and potentially included in relevant AI-generated answers, citations, comparisons and recommendations.

Within ProCited’s methodology, AI Visibility depends on a clear first-party Voice, strong entity understanding and credible third-party Echoes that support and corroborate that understanding across the wider web.

AI Visibility is not simply whether a webpage can be found. It also considers whether the entity can become relevant to the questions, conversations and answers that matter.

AI Visibility Audit

ProCited service

An AI Visibility Audit does not simply measure a website. It models AI’s current belief about an entity by creating a structured, point-in-time assessment of how selected AI platforms currently understand and represent it.

At ProCited, the Audit can review the entity’s website, content, controlled profiles, structured data, entity clarity, consistency, technical accessibility, digital evidence and selected AI-generated answers.

Selected baseline prompts may be used alongside this review to identify what is clear, missing, inconsistent or weak.

It is a consultancy assessment rather than an automated AI Visibility monitoring platform.

Explore the AI Visibility Audit

AI Visibility consultancy

An AI Visibility consultancy helps people, businesses, brands, products and services improve the clarity, consistency and digital evidence that can support how AI platforms discover, understand, describe, cite and potentially recommend them.

ProCited is an AI Visibility consultancy. It provides strategy, audits, conversation planning, voice and echo creation, and ongoing echo growth rather than an automated prompt-monitoring platform.

AI Visibility Optimisation (AIVO)

AI Visibility Optimisation (AIVO) is ProCited’s broader approach to strengthening how AI platforms discover, recognise, understand, describe, cite and potentially recommend people, businesses, brands, products and services.

At ProCited, AIVO brings together:

Generative Engine Optimisation (GEO);
Answer Engine Optimisation (AEO);
AI SEO;
AI search;
clear first-party Voice;
credible third-party Echoes;
entity understanding;
structured information;
answer-ready content;
digital evidence;
ongoing improvement.

AIVO looks beyond an individual webpage, prompt or search result. It considers the wider information environment surrounding an entity and how that information can help the entity become relevant to AI-generated questions, comparisons, explanations, citations, recommendations and answers.

AI Visibility Strategy Session

ProCited service

An AI Visibility Strategy Session is the first stage of the ProCited AIVO Method.

It clarifies what the person, business, brand, product or service wants to be known for, who it wants to reach, which AI conversations and answers matter and what outcomes the AI Visibility work should support.

The Strategy Session establishes the intended direction before the Audit and later work begin.

Explore the AI Visibility Strategy Session

AI web

ProCited practical term

The AI web is the connected network of webpages, profiles, datasets, publications, reviews, directories and other accessible sources through which an AI system may discover and understand an entity.

It is not a separate hidden website for machines. It is a practical way of describing the wider evidence environment beyond one company website.

AI-Generated Answer

An AI-Generated Answer is a response generated or synthesised by an AI system in response to a user’s question, instruction or prompt.

It may include explanations, summaries, comparisons, recommendations, brand mentions, links, citations or information drawn from one or more sources. The shorter expression AI answer is also commonly used.

Related: AI Citation; AI Mention; AI Source; Prompt

Answer Engine

An Answer Engine is a system that retrieves and interprets information to produce a direct, synthesised answer to a user’s question rather than only returning a list of webpages.

AI-powered answer engines may combine information from several sources and present citations or links alongside the response.

Answer Engine Optimisation (AEO)

Answer Engine Optimisation (AEO) is the practice of structuring and improving content, entity information and supporting evidence so answer engines can understand, retrieve and potentially use it when responding to relevant questions.

Within ProCited’s methodology, AEO focuses on helping an entity become part of the direct answer. It sits within the broader discipline of AIVO and works alongside on-site clarity and off-site corroboration.

Answer extraction

Answer extraction is the process of identifying and lifting a useful answer, fact or passage from a source.

Clear headings, direct first sentences and self-contained passages can make relevant information easier to extract, although they do not guarantee selection or citation.

B

Backlink

A backlink is a hyperlink from one webpage to another.

A backlink can also function as part of an echo when the surrounding context reinforces useful information about the correct entity, but an echo does not have to contain a backlink.

C

Canonical answer

A Canonical answer is the approved, concise answer a business wants to maintain for an important question.

It should be accurate, supportable and owned by one clear source page so other pages and external sources can reinforce it without creating contradictions.

Canonical entity page

A Canonical entity page is the main webpage that defines an organisation, person, product, service or location and connects it to its most important verified facts and related entities.

Citation

A citation is a reference to a business, person, product, service, location, idea or source.

In ProCited’s work, a citation is useful when it contributes accurate, relevant information that can be connected to the correct entity. An AI citation is the visible use of a source inside an AI-generated answer.

Citation readiness

Citation readiness is the degree to which a page contains clear, supportable and self-contained information that could be selected and referenced as a source.

Citation readiness can be improved, but no page can be guaranteed a citation.

Content Chunking

Content structuring practice

Content Chunking is the practice of organising information into clear, coherent and self-contained sections, with each section focused on a particular question, fact, subject or stage of an explanation.

Useful chunks normally include a descriptive heading, a direct opening answer and the supporting context needed to understand the passage without relying heavily on distant sections of the page.

Content Chunking can make information easier for people to scan and may also make relevant passages easier for search and AI systems to retrieve, extract and interpret.

It does not mean breaking writing into unnatural fragments or repeating the same answer across multiple sections.

Corroborate

ECHO Action Framework stage

Corroborate is the second stage of ProCited’s ECHO Action Framework.

It means creating, earning or strengthening relevant credible third-party evidence through profiles, citations, reviews, articles, interviews, directories, partnerships and other credible sources.

Corroboration

Corroboration is support for an understanding from additional, relevant sources.

It does not require identical wording. It requires compatible evidence that reinforces the same underlying facts, attributes or relationships.

D

Digital Evidence

Digital Evidence is information visible online that may help an AI system identify, classify, contextualise, corroborate or understand an entity.

It may be on-site or off-site, first-party or third-party. Its value depends on what it confirms, who publishes it, how current it is and how clearly it connects to the correct entity.

Digital Signal

A Digital Signal is a piece of online information that may contribute to how an AI system identifies, classifies, connects or understands an entity.

A signal may confirm a name, category, location, offering, expertise, relationship, reputation, activity or relevance. It becomes an echo when it provides useful and credible third-party reinforcement for an accurate part of the entity’s story.

E

Echo

Echo Principle term

Within The Echo Principle™, an Echo is a credible third-party digital signal that reinforces AI’s understanding of an entity.

An echo is defined less by its format than by the useful evidence it contributes. A profile, review, article, partner page, directory entry, interview or other credible third-party source may act as an echo when it reinforces accurate and relevant information.

ECHO Action Framework

ProCited framework

The ECHO Action Framework is ProCited’s four-stage framework for applying The Echo Principle™: Establish, Corroborate, Harmonise and Optimise.

It explains the actions used to strengthen entity understanding and digital evidence. It is not the same as the five-stage ProCited AIVO Method, which describes the sequence of ProCited’s consultancy services.

Echo Consistency

Echo Principle term

Echo Consistency is alignment in the underlying facts attached to an entity across different sources.

Wording and perspective can vary, but core details such as identity, category, location, relationships and offering should not conflict.

Echo Source

Echo Principle term

An Echo Source is the place where corroborating evidence appears, such as a publication, directory, review platform, podcast, professional profile, association website, partner page or independent publisher.

Related: Echo; Echo Type; Third-Party Source; Trusted Echo

Echo Type

Echo Principle term

Echo Type describes the subject or activity being reinforced, such as a product, service, person, event, award, partnership, location, piece of research, review or case study.

E-E-A-T

Google quality framework

E-E-A-T stands for Experience, Expertise, Authoritativeness and Trustworthiness.

It is a framework used within Google’s Search Quality Rater Guidelines to assess whether content and its creator demonstrate appropriate experience, subject knowledge, authority and trust.

E-E-A-T is not one individual ranking factor, and quality-rater assessments do not directly determine rankings. The framework is nevertheless useful when evaluating whether content is accurate, transparent, well-supported and created by an appropriate source.

Within AI Visibility, the same qualities may also improve the usefulness and credibility of the digital evidence available to AI systems.

Entity

An Entity is an identifiable thing that information can be connected to.

Within ProCited’s work, an entity may be a business, founder, professional, product, service, location, brand, organisation, development, event or idea.

Entity clarity

Entity clarity is the degree to which a source clearly states what an entity is, what it does, who or what it is connected to and how it differs from similarly named entities.

Entity Corroboration

Entity Corroboration is the reinforcement of AI’s understanding of an identifiable entity through relevant and credible third-party digital signals.

It is different from repeating the same claim across many pages. The supporting information should contribute useful evidence and connect clearly to the correct entity.

Entity one-liner

An Entity one-liner is a concise definition that names the official entity, its verified category, its audience or use case and its primary function or evidence-based differentiator.

Entity Recognition

Entity Recognition is the ability to identify an entity and correctly connect information, attributes and relationships to it.

Within The Echo Principle™, recognition comes before confidence and recommendation.

Related: AI Confidence; Entity; Recognition; Recommendation

Entity Retrieval Gap

ProCited term

Entity Retrieval Gap is a ProCited term describing a situation in which useful information about an entity exists or is indexed but is not reliably retrieved, connected to the correct entity or used when an AI system generates a relevant answer.

A page can therefore be accessible and indexed while the information it contains still fails to contribute to the AI-generated answer that matters.

The gap may occur at retrieval, entity recognition, information connection or answer-use stages.

The concept distinguishes traditional discoverability from actual inclusion in AI-generated answers.

Search can find the page. The information still has to be retrieved, connected and used.

Entity SEO

Informal industry term

Entity SEO is an informal term for improving the clarity, consistency and connections surrounding an identifiable entity so search engines and AI systems can more accurately recognise and understand it.

The work may include establishing a canonical entity page, maintaining consistent core facts, connecting related people, organisations, products, services and locations, adding appropriate structured data and strengthening relevant third-party corroboration.

Entity SEO focuses on the identifiable subject behind the webpages rather than only the keywords used on individual pages.

Within ProCited’s methodology, entity clarity is an important part of AI Visibility Optimisation, but AIVO extends beyond entity SEO to include conversation strategy, direct answers, credible third-party Echoes and ongoing growth.

Establish

ECHO Action Framework stage

Establish is the first stage of ProCited’s ECHO Action Framework.

It means defining the entity clearly: who or what it is, what it does, where it operates, who it serves and what it should be known for. A clear original voice gives other sources something accurate to reinforce.

Evidence status

Evidence status is a label that distinguishes the type and strength of support behind a claim, such as official guidance, published research, platform observation, internal experiment, editorial heuristic, hypothesis or unsupported claim.

F

First-party evidence

First-party evidence is evidence created or directly collected by the business or publisher, such as original data, testing, interviews, customer-approved case studies, screenshots, measurements or documented field experience.

First-Party Source

A First-Party Source is a source whose information is created or controlled by the entity itself.

This includes the official website, product and service pages, company profiles, press materials and business-controlled social profiles. First-party information establishes and distributes the original voice, but it is not the same as third-party corroboration.

G

Generative AI

Generative AI is artificial intelligence that can produce new content in response to an instruction or prompt. The output may include text, images, audio, video, code or other forms of content.

ProCited is primarily concerned with generative systems that produce answers, explanations, comparisons, citations and recommendations involving identifiable entities.

Generative Engine Optimisation (GEO)

Generative Engine Optimisation (GEO) is the practice of improving the visibility, use, attribution or citation of content in responses produced by generative engines.

Within ProCited’s methodology, GEO is one part of the broader AIVO discipline. GEO focuses on generated answers and source use, while AIVO also considers entity clarity, on-site information and off-site corroboration across the wider AI-discovery environment.

Ghost Citation

Attributed to Writesonic

A Ghost Citation occurs when an AI-generated answer cites or links to a business’s webpage as a source but does not mention or visibly attribute the information to the business or brand within the answer itself.

The content has contributed to the AI answer, and the webpage may appear within its citations or sources, but the reader may never see the name of the business that produced it.

The term is used in Writesonic’s Ghost Citation Study to distinguish between being cited as a source and receiving visible brand recognition.

Source note: This definition follows the AI Visibility meaning used in Writesonic’s Ghost Citation Study, as reported by Search Engine Land. The same phrase may be used differently in other fields.

Related: AI Citation; AI Mention; AI Source; Recognition

H

Harmonise

ECHO Action Framework stage

Harmonise is the third stage of ProCited’s ECHO Action Framework.

It means identifying and correcting conflicting information, connecting related entities and aligning the underlying facts while allowing each source to retain its own voice and perspective.

I

Independent Digital Signal

An Independent Digital Signal is online evidence created or published outside the entity’s direct control that reinforces a relevant fact, attribute or relationship connected to that entity.

ProCited evaluates independent signals according to accuracy, relevance, credibility, context, freshness and connection to the correct entity.

K

Knowledge graph

A Knowledge graph is a structured representation of entities and the relationships between them.

The concept helps explain why consistent identities, categories, locations and relationships can matter to machine understanding.

L

Large Language Model (LLM)

A Large Language Model (LLM) is a type of artificial intelligence model trained on large amounts of language data so it can process and generate language-based outputs.

LLMs can help power AI assistants and answer systems, but the model is not the same thing as the company, product or interface through which people use it.

Large Language Model Optimisation (LLMO)

Large Language Model Optimisation (LLMO) is a broad industry label for work intended to improve how content or entities are understood and represented by LLM-based systems.

Usage is not perfectly standardised. ProCited normally uses the more outcome-focused term AI Visibility Optimisation (AIVO).

llms.txt

Proposed web convention

llms.txt is a proposed Markdown file, normally located at /llms.txt, intended to help language models and AI applications identify important information and resources available on a website.

The file may provide a short description of the website and links to selected pages, documentation or clean Markdown versions of important content.

llms.txt is an emerging community proposal rather than a universally adopted web standard. Its presence does not guarantee that an AI platform will read it, use it, cite the website or improve the website’s AI Visibility.

It should complement clear webpages, accessible HTML, structured data, internal links and accurate content rather than replace them.

M

Mention Rate

AI Visibility metric

Mention Rate is the proportion of tested AI-generated answers in which a specified person, business, brand, product, service or other entity is explicitly mentioned.

The entity can be mentioned whether or not its website is cited as a source.

A Mention Rate is meaningful only within a clearly defined testing scope, including the AI platforms, prompts, dates, locations, number of tests and criteria used to identify a mention.

Mention Rate should therefore be interpreted separately from Citation Rate. A brand may be frequently mentioned without its website being cited, or cited without receiving strong visible attribution.

Source: Cloudflare AEO Visibility.

Model Context Protocol (MCP)

Named protocol

The Model Context Protocol (MCP) is an open standard for connecting AI applications and agents to external tools, data sources and workflows.

MCP primarily supports agent-to-tool and agent-to-data connections. It is related to, but different from, A2A protocols designed for communication between agents.

Multi-Agent System

A Multi-Agent System is an environment in which several specialised AI agents communicate and work together to achieve a shared or connected objective.

One agent might interpret the request, another search for options, another verify availability, another handle payment and another coordinate fulfilment.

O

Off-Site AI Visibility

Off-Site AI Visibility refers to the digital evidence, references and relationships that appear outside an entity’s own website and may help AI systems recognise, verify, contextualise or understand it.

Examples include controlled social profiles, directories, reviews, publications, interviews, podcasts, association pages, partner pages, event listings and customer discussions. Not all off-site evidence is independent, but many strong echoes live in credible third-party sources.

On-Site AI Visibility

On-Site AI Visibility refers to work carried out on an entity’s own website to make its identity, offering, relationships, expertise and relevance easier for people, search engines and AI systems to understand.

This may include clear entity definitions, useful content, answer-ready pages, consistent facts, internal links, structured data, accessible HTML, authorship and location information.

Ongoing Echo Growth

ProCited service

Ongoing Echo Growth is the fifth stage of the ProCited AIVO Method and the continuing consultancy service for expanding, updating and strengthening an entity’s Voice and credible Echoes over time.

It can expand into new questions, comparisons, explanations, recommendations and AI-generated answers, strengthen existing evidence, create new credible Echoes and keep important information current as markets, competitors, sources and AI platforms change.

Explore Ongoing Echo Growth

Optimise

ECHO Action Framework stage

Optimise is the fourth stage of ProCited’s ECHO Action Framework.

It means continually improving the quality, relevance, clarity, accuracy, freshness and reach of the corroborating signals surrounding the entity.

P

Part of the Conversation

ProCited phrase

Part of the Conversation is a ProCited phrase describing the goal of helping a person, business, brand, product or service become relevant and recognisable within the AI-generated conversations and answers that matter to its audience.

It does not mean appearing in every answer or being recommended for every question.

It means strengthening the clarity, relevance and credible evidence that can help an entity be considered, understood, mentioned, cited, compared or recommended when appropriate.

The question defines the conversation. The answer is where AI Visibility appears.

Passage optimisation

Passage optimisation is the practice of making an important section understandable on its own by naming the subject, answering the heading directly and keeping evidence and conditions close to the claim.

ProCited

ProCited entity

ProCited is an AI Visibility consultancy specialising in AI Visibility Optimisation (AIVO), GEO, AEO, AI SEO and AI search.

ProCited helps people, businesses, brands, products and services become part of the conversation AI is already having by strengthening the information and credible digital evidence that can help AI platforms discover, understand, describe, mention, cite, compare and potentially recommend them in relevant AI-generated answers.

Its work combines AI Visibility strategy, audits, conversation planning, a clear first-party Voice, credible third-party Echoes, entity understanding, structured information and ongoing improvement.

The ProCited Echo Principle™ explains the relationship between an entity’s first-party Voice, the credible third-party Echoes surrounding it and the confidence AI systems may form from that combined evidence.

ProCited AIVO Method

ProCited method

The ProCited AIVO Method is the five-stage consultancy process ProCited uses to help people, businesses, brands, products and services strengthen their AI Visibility.

The five stages are:

AI Visibility Strategy Session
AI Visibility Audit
AI Conversation Strategy
Voice and Echo Creation
Ongoing Echo Growth

The ProCited AIVO Method describes the consultancy journey.

The ECHO Action Framework separately describes how The Echo Principle™ is applied.

Prominence

AI Visibility metric

Prominence is a measure of how strongly and visibly a cited source or entity contributes to an AI-generated answer.

In AI Visibility measurement, prominence can consider how much of an answer is attributed to a cited source and how early or visibly that source appears within the response.

Prominence is different from Citation Rate. Citation Rate asks whether the source was cited; Prominence examines the strength or position of that cited contribution.

Because measurement methods can vary between platforms and tools, any Prominence result should state the methodology and testing scope used.

Source: Cloudflare AEO Visibility.

Prompt

A Prompt is the instruction or question given to an AI system.

Prompt wording, context, location, date, user state, available tools and the model or product being used can affect the answer produced.

Prompt monitoring

Prompt monitoring is the repeated testing and recording of selected prompts to track mentions, citations, errors, competitors, source changes and recommendation inclusion over time.

Reliable monitoring normally requires specialist third-party software. ProCited may use limited baseline prompt testing within an audit, but it does not provide an automated AI Visibility monitoring platform.

Prompt Visibility

ProCited practical term

Prompt Visibility is the degree to which a business, brand, person, product, service or other entity appears within the answers produced for a defined set of prompts.

A Prompt Visibility assessment may record mentions, citations, comparisons, recommendations, answer position, source use and competitor inclusion across selected AI platforms.

Prompt Visibility is always dependent on the testing scope. Results may change according to the prompts, platforms, models, locations, dates, user context and testing frequency included.

It should therefore be treated as a point-in-time observation rather than a universal measure of how every AI system understands an entity.

Q

Query fan-out

Query fan-out is a process in which a complex question is expanded into several related searches or sub-questions.

Content can prepare for this by clearly covering the supporting facts, entities and relationships needed to answer the broader question.

R

Recognition

Echo Principle stage

Recognition is the stage at which an AI system can identify an entity and understand enough about what it is, what it does and where it belongs.

In The Echo Principle™ sequence, recognition comes before confidence.

Recommendation

Echo Principle stage

Recommendation is the inclusion or suggestion of an entity in response to a relevant user question.

The Echo Principle™ can improve the available evidence, but it cannot guarantee that any AI system will cite or recommend a particular entity.

Reinforced Understanding

Echo Principle term

Reinforced Understanding is a clearer pattern formed when multiple relevant sources contribute compatible evidence about the same entity.

It is the opposite of relying on one isolated self-description.

Retrieval

Retrieval is the process of finding relevant information from websites, documents, databases or other sources so it can be used in an AI-generated answer.

Retrieval does not automatically mean the source will be cited or used. Clear, accessible and well-connected information can improve availability for retrieval without guaranteeing inclusion.

Retrieval-Augmented Generation (RAG)

Retrieval-Augmented Generation (RAG) is a method in which an AI system retrieves relevant information from external sources and supplies it to a language model when generating an answer.

RAG helps explain why accessible websites, clear entity information and credible external sources may influence an answer even when the information is not permanently contained in a model’s training data.

S

Schema markup

Schema markup is structured data vocabulary added to a webpage to describe visible content, entities, attributes and relationships more explicitly.

Schema can support understanding and feature eligibility, but it does not guarantee rankings, citations or recommendations and does not replace clear visible content or corroborating evidence.

Search Engine Optimisation (SEO)

Search Engine Optimisation (SEO) is the established practice of improving a website and its content so it can be crawled, understood and ranked more effectively in traditional search-engine results.

ProCited treats SEO as an important discoverability foundation but distinguishes it from AIVO, which also considers entity recognition, corroboration and inclusion in AI-generated answers across a wider body of digital evidence.

Semantic Consistency

Semantic Consistency is consistency of meaning across different sources even when the wording, format and perspective differ.

The goal is compatible understanding, not duplicated copy.

SEO for AI

Informal industry phrase

SEO for AI is an informal, plain-English expression used to describe work that helps a business, brand or website become more visible within AI-generated answers and AI-led search experiences.

It is often used as a simple way to explain AI Visibility Optimisation, Answer Engine Optimisation and Generative Engine Optimisation to people already familiar with traditional SEO.

However, SEO for AI is not exactly the same as conventional SEO. Traditional SEO commonly focuses on helping webpages become discoverable and rank in search results. SEO for AI also considers whether AI systems can understand the business, connect it with relevant questions, find supporting evidence, extract its information, mention or cite it and potentially include it in recommendations.

At ProCited, SEO for AI is a useful introductory description, while AI Visibility Optimisation describes the broader practice more accurately.

Source of truth

A Source of truth is the approved source that controls an important business fact, such as the official company name, service definition, product status, location, policy or current price.

Structured data

Structured data is machine-readable information embedded in or connected to a webpage or system.

Schema.org markup is a common form of structured data. Product feeds, APIs and protocol payloads may also provide structured information for search systems, AI applications and agents.

T

The Echo Principle™

ProCited methodology

The Echo Principle™ is an AI Visibility and entity-corroboration framework developed by ProCited.

It explains how a clear first-party Voice can be reinforced by credible third-party Echoes, supporting the progression Voice → Echoes → Recognition → Confidence → Recommendation.

Third-party corroboration

Third-party corroboration is supporting information published by a party other than the business itself, such as an industry publication, partner page, professional directory, review platform or independent profile.

Third-Party Source

A Third-Party Source is a source outside the entity’s direct control, such as an independent publication, customer review, industry association, partner site, podcast, event organiser or specialist directory.

Third-party status alone does not make a source valuable. Its information must still be relevant, accurate, current, credible and connected to the correct entity.

Trusted Echo

Echo Principle term

A Trusted Echo is a useful echo from a relevant and credible source that reinforces a correct understanding of an entity.

Trusted is practical shorthand for stronger supporting evidence, not a claim that AI systems trust in a human sense. Not every mention, link or repeated statement is a trusted echo.

V

Voice

Echo Principle term

Within The Echo Principle™, Voice is what an entity says about itself through the sources it controls, especially its website.

The voice establishes the original identity, offering, location, audience and position that other sources may reinforce.

Voice and Echo Creation

ProCited service

Voice and Echo Creation is the fourth stage of the ProCited AIVO Method.

It strengthens an entity’s own first-party Voice and creates or improves credible third-party Echoes that reinforce who or what the entity is, what it offers, who it serves and why it is relevant.

The objective is not identical wording across every source. It is consistent meaning supported by diverse, credible and correctly connected evidence.

Explore Voice and Echo Creation

Z

Zero AI Visibility

ProCited working definition

Zero AI Visibility is an assessment result in which a business records no relevant mentions, citations, comparisons or recommendations across the AI platforms, questions and testing conditions included in an AI Visibility assessment.

A business may rank prominently in conventional search results and still record Zero AI Visibility when customers ask AI platforms relevant questions about its products, services, expertise or market.

Zero AI Visibility does not mean that the business appears nowhere across every AI platform or every possible prompt. It means that no relevant visibility was identified within the defined scope of the assessment.

Zero-Click Search

A Zero-Click Search is a search interaction in which the user receives information or completes the search without clicking through to an external website.

A business may still be named, described, cited or recommended without receiving a visit. No click is not the same as no visibility.

Glossary review and updates

Last updated: 15 August 2026

This is a living glossary. ProCited reviews and updates definitions as AI-search terminology, platform behaviour, protocols and working practices change. During its early development, the glossary may be updated frequently before moving to a more regular review schedule.

Suggest a term or correction

AI terminology changes quickly. To suggest a missing term or correction, contact ProCited and include the term, your proposed definition and any authoritative source that supports the change.

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The language of AI Visibility — from answers to agents.

Core ProCited terms

How to use this glossary

How this differs from The Echo Principle glossary

A

Agent Interoperability

Agent-Ready Business

Agent-to-Agent Interaction

Agent2Agent Protocol (A2A)

Agentic AI

Agentic Commerce

Agentic Commerce Protocol (ACP)

Agentic Payment

Agentic Visibility

AI Agent

AI Assistant

AI Citation

AI Citation Rate

AI Confidence

AI Conversation Strategy

AI Crawlability

AI discovery

AI Invisibility

AI Mention

AI Mode

AI Noise

AI Optimisation (AIO)

AI Overview

AI search

AI SEO

AI Shopping Agent

AI Source

AI Visibility

AI Visibility Audit

AI Visibility consultancy

AI Visibility Optimisation (AIVO)

AI Visibility Strategy Session

AI web

AI-Generated Answer

Answer Engine

Answer Engine Optimisation (AEO)

Answer extraction

B

Backlink

C

Canonical answer

Canonical entity page

Citation

Citation readiness

Content Chunking

Corroborate

Corroboration

D

Digital Evidence

Digital Signal

E

Echo

ECHO Action Framework

Echo Consistency

Echo Source

Echo Type

E-E-A-T

Entity

Entity clarity

Entity Corroboration

Entity one-liner

Entity Recognition

Entity Retrieval Gap

Entity SEO

Establish

Evidence status

F

First-party evidence

First-Party Source

G

Generative AI

Generative Engine Optimisation (GEO)

Ghost Citation

H

Harmonise