Technical eligibility, representation and narrative integrity.
Customers and AI systems can only work with the information they can access and interpret. These definitions connect technical conditions, AI inclusion, source quality and representation risk to the wider customer decision environment without implying that SI controls external platforms.
66. Technical Integrity
Technical and governance domain · SI-DEF-066It means the technical foundation can support discovery, trust and action without hidden degradation.
Technical Integrity is the condition in which the systems, infrastructure, code, delivery paths and controls supporting search-led discovery and customer journeys operate reliably, accessibly, accurately and consistently enough to preserve decision confidence and commercial performance.
Where it fits: A cross-functional domain observed by Search Intelligence and typically executed by SEO, engineering, infrastructure, platform and product teams.
Eligibility, accessibility, rendering, performance, network delivery, structured information, security-relevant reliability, monitoring and change control.
Not limited to page speed, technical SEO or one audit score.
Includes crawl, render, index, network, uptime, performance, error and journey data with scope and confidence.
Technical failures can create missed, failed or confidence-weakening journeys and therefore require materiality and ownership.
67. Network Layer Performance Degradation
Technical risk condition · SI-DEF-067The network path becomes slower, unstable or less reliable.
Network Layer Performance Degradation is a measurable decline in the reliability, latency, routing, delivery or availability of network-dependent services that can impair search access, rendering, journey performance or customer confidence.
Where it fits: A subtype of Technical Integrity exposure that may sit outside the website application itself.
DNS, routing, origin reachability, CDN behaviour, latency, packet loss, regional delivery and intermittent availability.
Broader than an ISP-specific issue and should not be claimed without network evidence.
Reported through repeatable network measurements, time, location, path, comparison and impact evidence.
Enables correct ownership across infrastructure, hosting, network, vendor or platform teams.
68. Search Eligibility
Technical and search construct · SI-DEF-068The asset is able to compete for inclusion.
Search Eligibility is the condition in which a digital asset meets the technical and policy requirements necessary to be considered for inclusion or presentation within a search experience.
Where it fits: A prerequisite within SEO and technical integrity before Organic Search exposure can occur.
Crawl access, rendering, indexability, content availability, policy compliance and feature-specific requirements.
Eligibility does not guarantee ranking, inclusion, citation or traffic.
Reported through technical tests, index evidence, search-engine diagnostics and observed inclusion conditions.
Loss of eligibility can create missed exposure and requires timely technical ownership.
69. AI Visibility
AI and representation construct · SI-DEF-069It answers whether the brand or evidence appeared in the AI response.
AI Visibility is the observed or measured inclusion, mention, citation or presence of an organisation, product, source or claim within an AI-generated experience.
Where it fits: An exposure measure within AI Search Exposure and is narrower than AI Narrative Integrity.
Mentions, recommendations, citations, source links, product inclusion and comparison presence.
Does not establish accuracy, trust, preference, narrative integrity or commercial value.
Reported with platform, prompt, date, market, account state, response evidence and known variability.
May trigger representation, omission and source-of-truth governance review.
70. AI Search Exposure
AI and customer-environment construct · SI-DEF-070It describes what the AI search environment made available to the customer.
AI Search Exposure is the availability, absence, displacement or representation of an organisation or relevant evidence within an AI-enabled search or discovery experience.
Where it fits: A specialised form of Search Exposure within the Organic Search and Discovery Environment or wider decision environment.
AI mentions, recommendations, citations, supporting links, summaries, comparisons, omissions and competitor occupation.
Does not include every AI interaction and does not prove an encounter or Search Moment.
Reported using exposure-state taxonomy, reproducible prompts where possible, dates, platforms, context and variability.
Identifies AI-specific presence and representation conditions requiring ownership.
71. AI Narrative Integrity
AI representation and governance domain · SI-DEF-071It asks whether AI tells the organisation's story accurately and responsibly.
AI Narrative Integrity is the degree to which AI-generated representations of an organisation, product or category are accurate, complete enough for the decision context, consistently supported by reliable sources and unlikely to create material misunderstanding.
Where it fits: Evaluates representation after or alongside AI Search Exposure and connects to Source-of-Truth Governance.
Accuracy, omission, context, source support, consistency, claims, comparison framing and decision consequence.
Not the same as AI Visibility and does not imply control over the AI platform.
Reported through captured outputs, source analysis, comparison, repeat testing, evidence confidence and materiality.
Identifies trust, reputation, customer and compliance exposures created by AI representation.
72. Narrative Integrity
Representation construct · SI-DEF-072The story customers encounter matches the evidence and does not mislead by contradiction or omission.
Narrative Integrity is the degree to which the facts, claims, explanations and context used to represent an organisation remain accurate, coherent, supportable and consistent across decision-relevant sources and experiences.
Where it fits: The broader representation principle of which AI Narrative Integrity is one domain.
Owned content, publisher material, reviews, product information, AI outputs, comparisons, claims and source consistency.
Not message uniformity, brand tone or reputation positivity at any cost.
Assessed through source comparison, claim validation, contradiction, omission and decision-consequence analysis.
Protects trust and enables accountable correction of distorted or inconsistent representation.
73. Source-of-Truth Governance
Governance domain · SI-DEF-073It governs which facts are authoritative and how they stay reliable everywhere they are used.
Source-of-Truth Governance is the system of ownership, validation, approval, update and distribution controls used to keep authoritative organisational facts accurate, current, consistent and available to people and machines.
Where it fits: Supports Narrative Integrity, AI Narrative Integrity, Trust Architecture and technical representation.
Product facts, fees, policies, credentials, locations, claims, structured data, reference content, ownership and change control.
Not one webpage or database unless that asset is formally governed as part of the system.
Reported through source ownership, approval status, update cadence, conflicts, downstream propagation and exceptions.
Reduces distortion, omission and contradiction across search and AI environments.
74. Search Representation
Representation construct · SI-DEF-074It is how the search environment portrays the organisation.
Search Representation is the way an organisation, product, claim or source is presented, framed or omitted within search-led results and discovery experiences.
Where it fits: An observed condition within Search Exposure that may produce trust or influence effects.
Titles, snippets, result features, knowledge panels, AI summaries, reviews, publisher framing, comparison content and omissions.
Not limited to owned content or ranking position.
Reported through captured result evidence, comparison, accuracy assessment and exposure taxonomy.
Representation may require action from SEO, content, product, brand, PR, legal, compliance or source owners.
75. Representation Risk
Governance risk construct · SI-DEF-075It is the risk that what customers see creates the wrong understanding.
Representation Risk is the possibility that inaccurate, incomplete, weak, conflicting or misleading representation within search-led environments causes material loss of trust, preference, demand, reputation or compliance confidence.
Where it fits: Arises from Search Representation and is assessed through Narrative Integrity and materiality.
Distorted exposure, outdated facts, conflicting claims, negative framing, unsupported summaries and source weakness.
Not every unfavourable opinion or competitor comparison.
Reported with captured representation, source analysis, plausible consequence, confidence and owner.
Creates a formal basis for source correction, communication, escalation or accepted risk.
76. Omission Risk
Representation risk construct · SI-DEF-076Important evidence is missing when the customer or AI system needs it.
Omission Risk is the possibility that absent or insufficient decision-relevant information causes customers or systems to form a materially incomplete, unfavourable or unsafe understanding.
Where it fits: A subtype of Representation Risk and may create missed, weak or distorted exposure.
Missing product facts, exclusions, proof, credentials, context, sources, comparisons, safety information and brand inclusion.
Not every missing detail; the omission must be relevant to the decision context.
Reported through required-evidence gaps, source audits, AI output comparison, customer questions and materiality.
Assigns ownership for creating, publishing and maintaining missing evidence.
Use the public Diagnostic for orientation, an executive conversation for scoping or a paid…
See whether AI systems represent the organisation accurately and with credible source…
Search the complete approved SI definitions for architecture, customer decisions, evidence,…