Knowledge Structuring Model

The Research Behind the KSM Model™

What it is

The Knowledge Structuring Model (KSM™ home) is an open, citable framework for measuring how findable a brand is across generative AI systems. Where SEO measures rank in search results, KSM Model™ measures whether a brand is the answer the model gives.

The research behind KSM™ — a socio-technical framework for AI visibility, connecting knowledge graphs, information retrieval, entity authority, and citation trust around the SSRN working paper.

Research program

The program now spans four publications. KSM™ is the foundational framework for AI-mediated visibility and citation authority; it is extended by Warrant Clearing (reasoning integrity across agentic synthesis) and EKR (enterprise knowledge readiness), and grounded in the origin research on AI's impact on service centers.

One connected enterprise AI framework: stage one KSM™ AI visibility, stage two EKR enterprise knowledge readiness, stage three Warrant Clearing governed agentic AI.

Publications

KSM™Knowledge Structuring Model™

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

The foundational framework for measuring and improving AI visibility.

SSRN 6721140 · Zenodo archive (10.5281/zenodo.20766821)

Distributed across SSRN's Generative AI Special Topic Hub (Vol. 4, Issue 111), Behavioral Marketing Journal (Vol. 18, No. 91), and Journal of Managerial Marketing (Vol. 18, No. 88).

WARRANTWarrant Clearing for Artificial Intelligence Agents

Chaudry, J., & Bowen, A. Q. (2026). Maintaining Justified Claims Across Recursive Agentic Synthesis. SSRN Electronic Journal. DOI: 10.2139/ssrn.6899418.

Keeps claims justified, traceable, and policy-aligned throughout autonomous agent workflows.

SSRN 6899418

Distributed across CompSciRN Computer Science Education, CompSciRN Software Engineering, CompSciRN Information Systems, and InfoSciRN Generative AI.

EKRBeyond AI Visibility: Extending KSM™ to Enterprise Knowledge Readiness

Bowen, A. Q. (2026). Beyond AI Visibility: Extending KSM™ to Enterprise Knowledge Readiness (EKR). SSRN Electronic Journal, Abstract ID 7113181.

Prepares internal enterprise knowledge to be structured, authoritative, permissioned, and agent-ready.

SSRN 7113181 · Zenodo archive (10.5281/zenodo.21680112)

Distributed across Entrepreneurship & Management, Management of Innovation, and Organizations & Markets: Policies & Processes networks, with distribution to Information Systems scheduled.

ORIGINThe Transformation of Service Centers

Bowen, A. Q. (May 17, 2025). The Transformation of Service Centers: A Reviewed Analysis of AI's Intelligence Impact and Evolving Landscape. SSRN, Abstract ID 6953758.

The origin research that surfaced the visibility gap KSM™ was built to measure.

SSRN 6953758

Origin & authorship

The KSM Model™ standard was authored by Dr. Anthony Q. Bowen and published in 2026. The full framework, weighting rationale, and validation methodology are available in the working paper hosted on SSRN.

Full Research Program →

Three pillars, one score

KSM Model™ combines three pillars — Structured Extractability (SE), Entity Salience (ES), and Citation Authority (CA) — into a single 0–100 score and a letter grade. The methodology page details each signal and how the math is composed.

Citation

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

Trademark & use

KSM Model™ and "Knowledge Structuring Model" are trademarks of the standard's author. The framework is free to reference and cite. Producing or publishing a KSM Model™ score on behalf of a third party requires attribution to the standard and the SSRN paper.