Systems analysis demonstrates an operational post-quantum cryptographic governance architecture for artificial intelligence pipelines, highlighting verifiable quantum risk certification.
This paper makes two contributions simultaneously. First, it introduces the Quantum Confidence Rating (QCR) — the first published measurement standard for post-quantum cryptographic compliance of artificial intelligence pipelines. QCR quantifies the proportion of AI system cryptographic primitives verified as compliant with NIST FIPS 203, 204, and 205, BSI TR-02102, and CNSA 2.0. QCR-Zero designates architectures where quantum cryptographic compromise of the AI pipeline is structurally impossible by design. QQL translates the Quantum Confidence Deficit into a measurable liability variable for regulators and insurers under DORA, eIDAS 2.0, CNSA 2.0, and the EU Product Liability Directive. These three standards constitute the fifth certification product family (C13/C14/C15) of the YIN-AI Governance Architecture, extending the canonical layer count from 63 to 66. Second, this paper demonstrates that the YIN-AI Governance Architecture is the deployed operational counterpart to the governance stack described in Quantum Technology Governance II (Aboy, Corrales Compagnucci, and Minssen, eds., Springer Nature Singapore, 2026, DOI: 10.1007/978-981-92-3768-5) as architecturally necessary but not yet built. The volume describes what a governance stack for quantum technologies must look like. It does not reference a deployed system that already embodies those properties. This paper demonstrates that system exists. For each of the six chapters' theoretical frameworks, this paper names the specific architectural component, published academic standard, or patent application that gives that framework operational form — already deployed, independently citable, and verifiable offline by any regulatory body, court, or research institution without vendor access. The YIN-AI Governance Architecture now encompasses 66 layers across five product certification families: YIN-AI CERTIFICATION (ACR/ACR-Zero/AQL, C1-C3), YIN-AI AUDITCHAIN (CCR/CCR-Zero/CQL, C4-C6), YIN-AI PROOFCHAIN (PCR/PCR-Zero/PQL, C7-C9), YIN-AI CYBERATTACK SHIELD (YCR/YCR-Zero/YEL, C10-C12), and YIN-AI QUANTUM CERTIFICATION (QCR/QCR-Zero/QQL, C13-C15). All standards are published under CC BY-NC-ND 4.0 International with confirmed Zenodo DOIs and a priority date of November 23, 2025.
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Ilyes Tarik MAZARI (2026) studied this question.
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