An open standard for quantifying AI security risk in entities subject to insurance underwriting. Five weighted scoring domains. Twenty-five discrete risk factors. Four rating tiers that map directly to underwriting decisions.
The AI Insurance Readiness Score (AIRS) is an open standard specification for quantifying artificial intelligence security risk in entities subject to insurance underwriting. AIRS defines five weighted scoring domains encompassing twenty-five discrete risk factors, a composite scoring methodology producing scores on a 0–100 scale, and four rating tiers that map directly to underwriting decisions. This specification provides the complete methodology, scoring rubrics, rating tier definitions, assessment process requirements, and conformance criteria necessary for institutional adoption by carriers, reinsurers, regulators, and enterprise risk teams.
Published by AI Security Intelligence LLC · April 2026 · Jurisdiction: United States of America
AIRS evaluates five thematic areas of AI security risk, each composed of five discrete factors. Domain weights reflect the relative contribution of each area to overall AI insurability.
Training data provenance, adversarial robustness testing, model versioning & rollback, poisoning detection, drift monitoring.
Human-in-the-loop oversight, hallucination controls, bias & fairness testing, output auditability, content provenance.
Model card & vendor documentation, third-party AI risk, API key governance, foundation-model dependency mapping, sub-processor controls.
NIST AI RMF alignment, ISO/IEC 42001 conformance, EU AI Act readiness, state AI law monitoring, GDPR/CCPA AI-specific controls.
AI incident response plan, recovery time objectives, AI-specific tabletop exercises, inter-system failure modes, business continuity for AI-dependent workflows.
Domain averages (1.0–5.0 scale) are weighted, summed, and multiplied by 20 to produce the composite AIRS score used for tier classification.
AIRS composite scores map to four rating tiers, each with a specific underwriting implication. The tier structure is designed to align with the decision architecture of institutional carriers and reinsurers.
| Score Range | Tier | Classification | Underwriting Signal |
|---|---|---|---|
| 80–100 | Tier 1 | AI Insurance Ready | Broadest coverage, premium discounts |
| 60–79 | Tier 2 | Conditionally Insurable | Coverage with exclusions or sub-limits |
| 40–59 | Tier 3 | Elevated Risk | Limited coverage, mandatory remediation |
| 20–39 | Tier 4 | Uninsurable | Coverage denied pending remediation |
The theoretical minimum AIRS score is 20 (all factors at maturity level 1). See Section 7 of the specification for the complete formula.
The specification is free to read, cite, and build upon. These paths help carriers, enterprises, and regulators apply AIRS to their own operations.
Evaluate your organization against all 25 AIRS factors using our free self-assessment calculator. Receive your composite score, tier classification, and prioritized remediation guidance.
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AIRS v1.0 is published as an open standard. Organizations may freely reference, implement, and build upon the methodology for internal risk assessment, underwriting, regulatory compliance, and academic research.
© 2026 AI Security Intelligence LLC. All rights reserved. This specification is published as an open standard. Organizations may freely reference, implement, and build upon the AIRS methodology for internal risk assessment, underwriting, regulatory compliance, and academic research, provided that attribution is given to AI Security Intelligence LLC and the standard version is cited. Reproduction or redistribution of this document in its entirety requires prior written permission from AI Security Intelligence LLC.
Attribution requirement: Any organization publishing AIRS scores, referencing AIRS tiers in policy language, or citing AIRS methodology in regulatory filings shall include the following attribution: "Scored using the AI Insurance Readiness Score (AIRS) v1.0 methodology, published by AI Security Intelligence LLC."
Comments, errata, and implementation inquiries: standards@aisecurityintelligence.com
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