Skip to main content

New: Take the KSM™ AI Visibility Assessment and identify what is limiting your visibility in AI-generated answers. Start now

The KSM™ Framework

One model for whether AI can understand, recognize, and cite you.

KSM™ is a socio-technical framework created by Dr. Anthony Q. Bowen that treats AI visibility as the product of three interdependent pillars rather than a list of tactics.

AI Visibility = f(E × S × C)

Extractable Structured Content · Entity Salience · Citation Authority

Three pillars · one system

The pillars multiply. The weakest one governs the outcome.

Because the pillars are multiplicative, strong content cannot compensate for an ambiguous entity, and a well-modeled entity cannot compensate for absent independent corroboration.

The three pillars of the Knowledge Structuring Model: Extractable Structured Content at 40 percent, Entity Salience and Knowledge Graph Alignment at 40 percent, and Citation Authority Reinforcement at 20 percent, combining into an AI visibility score.
The KSM™ three-pillar system. AI visibility is a product of the pillars, so the weakest pillar constrains the whole score.
  1. 01E · 40%

    Extractable Structured Content

    Can AI understand you?

    Measures how clearly machines can access, parse, and extract your knowledge from page structure, schema, metadata, FAQs, evidence blocks, and crawlable content.

  2. 02S · 40%

    Entity Salience and Knowledge Graph Alignment

    Can AI recognize you?

    Measures whether your brand, people, products, research, and identifiers form a consistent, connected, and unambiguous entity across your site and authoritative external sources.

  3. 03C · 20%

    Citation Authority Reinforcement

    Can AI trust and cite you?

    Measures whether independent publications, scholarly sources, media, industry references, and third-party applications reinforce your claims and authority.

The pillars multiply rather than add: a weak pillar constrains the entire score. Weights are fixed at 40 / 40 / 20 across every KSM™ assessment.

Plain language

KSM™ Explained Simply

Three questions, asked in order. If AI cannot understand your knowledge, recognition never happens. If it cannot recognize your entity, citation never happens.

KSM explained in simple terms: can AI understand you, can AI recognize you, and can AI trust and cite you.
KSM™ in plain language: understanding, recognition, and trust — in that order.

Signals

What each pillar examines.

E · 40%

Extractable Structured Content

Can AI understand you?

Measures how clearly machines can access, parse, and extract your knowledge from page structure, schema, metadata, FAQs, evidence blocks, and crawlable content.

  • Machine-readable page structure and heading hierarchy
  • Valid, linked JSON-LD that matches visible content
  • Evidence blocks, definitions, and answerable FAQ content
  • Crawlable, server-rendered critical copy

S · 40%

Entity Salience and Knowledge Graph Alignment

Can AI recognize you?

Measures whether your brand, people, products, research, and identifiers form a consistent, connected, and unambiguous entity across your site and authoritative external sources.

  • Consistent organization, people, and product naming
  • Stable entity identifiers reused across properties
  • Knowledge-graph alignment with authoritative external sources
  • Disambiguation from similarly named entities

C · 20%

Citation Authority Reinforcement

Can AI trust and cite you?

Measures whether independent publications, scholarly sources, media, industry references, and third-party applications reinforce your claims and authority.

  • Independent publications and media references
  • Scholarly and research citations
  • Industry references and third-party applications
  • Corroboration of claims outside your own domain

Framework identity

A citable framework with a stable identifier.

The framework is published, versioned, and citable. It is identified as https://ksmmodel.ai/#ksm-framework and is creator-linked to Dr. Bowen's Person entity at https://dranthonyqbowen.com/#person.

Bowen, A. Q. (2026). The Knowledge Structuring Model (KSM™): A Socio-Technical Framework for AI-Mediated Visibility and Citation Authority. SSRN Working Paper 6721140.