The language of AI Visibility — from answers to agents.

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.

Related: Agent2Agent Protocol (A2A); Agent-to-Agent Interaction; Model Context Protocol (MCP); Multi-Agent System

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.

Related: Agentic Visibility; Agentic Commerce; Structured data; Structured data

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.

Related: Agent2Agent Protocol (A2A); Agent Interoperability; Multi-Agent System; Agentic Commerce

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.

Related: Agent-to-Agent Interaction; Agent Interoperability; Model Context Protocol (MCP); Multi-Agent System

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.

Related: AI Agent; Agentic Commerce; Multi-Agent System; Multi-Agent System

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.

Related: AI Shopping Agent; Agentic Payment; Agentic Visibility; Agent-Ready Business

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.

Related: Agentic Commerce; AI Shopping Agent; Agentic Payment; Structured data

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.

Related: Agentic Commerce; AI Shopping Agent; Agentic Commerce; AI Agent

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.

Related: AI Visibility; Agent-Ready Business; Agentic Commerce; AI Shopping 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.

Related: AI Assistant; Agentic AI; Agentic Commerce; Multi-Agent System

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.

Related: AI Agent; Large Language Model (LLM); Prompt; Answer Engine

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.

Related: AI Mention; AI Source; Citation Readiness; Ghost Citation

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.

Related: Corroboration; Entity Recognition; Recognition; Trusted Echo

AI Conversation Strategy is the ProCited service that defines which questions, subjects, comparisons and recommendations a business wants to become part of.

It identifies the customers the business wants to reach, the facts and expertise that matter, the strongest supportable answers and the conversations where visibility would create genuine business value.

Related: AI Visibility Strategy Session; Canonical answer; Part of the Conversation; Voice and Echo Creation

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.

Related: AI search; AI Visibility; Part of the Conversation; Zero-Click Search

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.

Related: AI Visibility; Digital Evidence; Entity clarity; Off-Site AI Visibility

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.

Related: AI Citation; AI-Generated Answer; AI Visibility; Ghost Citation

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.

Related: AI Overview; AI Visibility Optimisation (AIVO); Answer Engine Optimisation (AEO); Generative Engine Optimisation (GEO)

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.

Related: AI-Generated Answer; AI citation; AI search; Zero-Click Search

AI search is a search or discovery experience in which an AI system generates or synthesises an answer rather than presenting only a conventional list of links.

Related: AI-Generated Answer; AI discovery; Answer Engine; Generative AI

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.

Related: AI Agent; Agentic Commerce; Agentic Payment; Agentic Visibility

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.

Related: AI Citation; AI-Generated Answer; AI Overview; Retrieval

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

Within ProCited’s methodology, AI Visibility depends on both the entity’s own clear voice and the relevant digital evidence that supports and corroborates it across the wider web.

Related: AI Invisibility; AI Visibility Optimisation (AIVO); Off-Site AI Visibility; On-Site AI Visibility

An AI Visibility Audit is a structured assessment of the information and signals that may influence how AI systems discover and understand a business.

At ProCited, the audit primarily reviews the business’s existing website, content, controlled profiles, structured data, entity clarity, consistency, technical accessibility and current off-site evidence. Selected baseline prompts may be tested to observe current answers, but prompt testing is only one small part of the audit.

Related: AI Visibility Strategy Session; Digital Evidence; Entity clarity; Prompt monitoring

An AI Visibility consultancy helps organisations improve how AI platforms discover, understand, describe, cite and 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.

Related: AI Visibility; AI Visibility Optimisation (AIVO); ProCited AIVO Method; Prompt monitoring

AI Visibility Optimisation (AIVO) is the practice of improving the clarity, accessibility, consistency and digital evidence that helps AI systems discover, recognise, understand and potentially recommend an entity.

At ProCited, AIVO combines on-site entity clarity, a defined conversation strategy, credible off-site echoes and ongoing growth. It is broader than optimising a single page for a single answer.

Related: AI Visibility; Answer Engine Optimisation (AEO); Generative Engine Optimisation (GEO); ProCited AIVO Method

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

It clarifies what the business wants to be known for, which customers it wants to reach, the outcomes it wants AI Visibility to support and the scope of the audit and later work.

Related: AI Conversation Strategy; AI Visibility Audit; ProCited AIVO Method

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.

Related: Digital Evidence; Off-Site AI Visibility; Retrieval; Voice

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

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.

Related: AI-Generated Answer; AI search; Answer Engine Optimisation (AEO); Retrieval

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.

Related: AI Visibility Optimisation (AIVO); Answer Engine; Generative Engine Optimisation (GEO); Part of the Conversation

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.

Related: Canonical answer; Citation readiness; Passage optimisation; Retrieval

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.

Related: Citation; Echo; Off-Site AI Visibility; Third-Party Source

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.

Related: AI Conversation Strategy; Answer extraction; Canonical entity page; Source of truth

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.

Related: Canonical answer; Entity; Entity clarity; Source of truth

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.

Related: AI citation; Backlink; Citation readiness; Corroboration

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.

Related: AI citation; Answer extraction; Passage optimisation; Retrieval

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

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

Related: Corroboration; ECHO Action Framework; Independent Digital Signal; Trusted Echo

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.

Related: Corroborate; Entity Corroboration; Third-party corroboration; Trusted Echo

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.

Related: Digital Signal; First-Party Source; Independent Digital Signal; Third-Party Source

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 independently reinforces a useful and accurate part of the entity’s story.

Related: Digital Evidence; Echo; Entity; Independent Digital Signal

Within The Echo Principle™, an Echo is an independent 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 source may act as an echo when it reinforces accurate and relevant information.

Related: Digital Signal; Echo Source; Echo Type; Trusted Echo

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.

Related: Corroborate; Establish; Harmonise; Optimise; ProCited AIVO Method

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.

Related: Echo; Harmonise; Semantic Consistency; Source of truth

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

Related: Echo; Echo Source; Trusted Echo; Voice and Echo Creation

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.

Related: Canonical entity page; Entity clarity; Entity Corroboration; Entity Recognition

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.

Related: Canonical entity page; Entity; Entity one-liner; Source of truth

Entity Corroboration is the reinforcement of AI’s understanding of an identifiable entity through independent, relevant and credible 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.

Related: Corroboration; Entity; Independent Digital Signal; The Echo Principle™

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.

Related: Canonical entity page; Entity clarity; Source of truth; Voice

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

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.

Related: ECHO Action Framework; Entity clarity; Source of truth; Voice

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.

Related: Digital Evidence; First-party evidence; Third-party corroboration

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.

Related: Digital Evidence; Evidence status; First-Party Source; Third-party corroboration

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 independent corroboration.

Related: Digital Evidence; First-party evidence; Third-Party Source; Voice

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.

Related: AI-Generated Answer; AI search; Large Language Model (LLM); Prompt

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.

Related: AI Visibility Optimisation (AIVO); Answer Engine Optimisation (AEO); Generative AI; Retrieval

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; Brand Visibility

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.

Related: Echo Consistency; ECHO Action Framework; Semantic Consistency; Source of truth

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.

Related: Digital Evidence; Digital Signal; Echo; Third-Party Source

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.

Related: Entity; Entity Recognition; Schema markup; Structured data

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.

Related: AI Assistant; Generative AI; Large Language Model Optimisation (LLMO); Retrieval-Augmented Generation (RAG)

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).

Related: AI Visibility Optimisation (AIVO); Generative Engine Optimisation (GEO); Large Language Model (LLM)

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.

Related: Agent2Agent Protocol (A2A); Agent Interoperability; AI Agent; Structured data

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.

Related: AI Agent; Agent-to-Agent Interaction; Agent Interoperability; Agentic Commerce

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.

Related: Digital Evidence; On-Site AI Visibility; Third-Party Source; Trusted Echo

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.

Related: Entity clarity; Off-Site AI Visibility; Schema markup; Voice

Ongoing Echo Growth is the fifth stage of the ProCited AIVO Method and the continuing monthly consultancy service.

It builds new echoes, strengthens existing ones, expands into new questions and opportunities, and keeps important information current. It is consultancy work, not an automated AI Visibility monitoring platform.

Related: ProCited AIVO Method; Prompt monitoring; Trusted Echo; Voice and Echo Creation

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.

Related: ECHO Action Framework; Ongoing Echo Growth; Trusted Echo

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

It does not mean controlling every answer or being recommended for every question. It means establishing enough clarity, relevance and corroborating evidence to be considered, mentioned, cited or recommended when appropriate.

Related: AI Conversation Strategy; AI Visibility; Recommendation; The Echo Principle™

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.

Related: Answer extraction; Canonical answer; Citation readiness; Retrieval

The ProCited AIVO Method is the five-stage consultancy process ProCited uses to help a business improve its AI Visibility.

The stages are: AI Visibility Strategy Session → AI Visibility Audit → AI Conversation Strategy → Voice and Echo Creation → Ongoing Echo Growth. The method describes the service journey; the ECHO Action Framework separately describes how The Echo Principle™ is applied.

Related: AI Visibility Optimisation (AIVO); AI Visibility Strategy Session; ECHO Action Framework; Ongoing Echo Growth

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.

Related: AI-Generated Answer; AI Assistant; 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.

Related: AI Visibility Audit; AI mention; Prompt; Recommendation

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.

Related: Answer Engine; Passage optimisation; Retrieval

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.

Related: AI Confidence; Entity Recognition; Recommendation; The Echo Principle™

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.

Related: AI mention; Part of the Conversation; Recognition; The Echo Principle™

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.

Related: Corroboration; Echo Consistency; Entity Corroboration; Trusted Echo

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.

Related: AI citation; Answer Engine; Query fan-out; 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.

Related: Large Language Model (LLM); Retrieval; Source of truth

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.

Related: Knowledge graph; On-Site AI Visibility; Structured data

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.

Related: AI Visibility Optimisation (AIVO); Answer Engine Optimisation (AEO); On-Site AI Visibility

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.

Related: Echo Consistency; Harmonise; Source of truth

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.

Related: AI Visibility Optimisation (AIVO); Answer Engine Optimisation (AEO); Generative Engine Optimisation (GEO); Search Engine Optimisation (SEO)

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.

Related: Canonical answer; Canonical entity page; Entity clarity; Semantic Consistency

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.

Related: Agent-Ready Business; Knowledge graph; Schema markup

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 relevant independent Echoes, supporting the progression Voice → Echoes → Recognition → Confidence → Recommendation.

Related: ECHO Action Framework; Entity Corroboration; Trusted Echo; Voice

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.

Related: Corroboration; Independent Digital Signal; Third-Party Source; Trusted Echo

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.

Related: First-Party Source; Independent Digital Signal; Third-party corroboration; Trusted Echo

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.

Related: Corroboration; Echo; Echo Source; Third-Party Source

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.

Related: First-Party Source; The Echo Principle™; Voice and Echo Creation

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

It strengthens the business’s own clear source of truth and creates or improves credible online signals that support the business’s place in the relevant AI conversations defined by its strategy.

Related: AI Conversation Strategy; Ongoing Echo Growth; ProCited AIVO Method; Trusted Echo; Voice

Zero AI Visibility is a measured state 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.

Related: AI Invisibility; AI Mention; AI Citation; AI Visibility Audit

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.

Related: AI-Generated Answer; AI Overview; AI Visibility; Zero AI Visibility