The audit binder is a snapshot of a moving system. Continuous evidence accumulates as AI decisions happen — so an audit becomes a query, not a project.
Enterprise AI & Engineering Insights — Page 7
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A chat export will not survive scrutiny. What a defensible AI production needs: completeness, integrity, and an export the other side can verify offline.
Institutional memory AI for manufacturing: index equipment manuals, drawings, and CMMS / EAM / QMS records with multimodal retrieval before the retirement wave.
ISO 42001 is a voluntary management standard; the EU AI Act is law. Where they overlap, where they diverge, and how one control set can satisfy both.
Completeness and disclosure are separate decisions: keep one tamper-evident AI ledger and scope what the user, regulator, auditor, and engineer each see.
HIPAA-compliant healthcare RAG: permission-aware retrieval, PHI audit logging, de-identified ingestion, and human review for every high-stakes clinical answer.
Institutional memory AI for financial services: domain filters at retrieval, veteran-verified calibration, and a five-element audit trail on every answer.
You can't govern AI you can't list. A model registry catalogs every model you run — purpose, data, limits, version, owner — and stays current as models change.
A DPIA written in Word is stale by the next sprint. Grounded in access, redaction and retention the runtime enforces, it stays current as processing changes.
Compliance-first RAG for banking and insurance: audit trails, permission-aware retrieval, and model risk management designed in from day one, not retrofitted.
The Annex IV technical file is usually reconstructed by hand from memory. Most of it can be assembled from what the system already records — and stay current.
Article 50 requires telling people when AI is involved. Generating the disclosure wherever AI was used — and recording it — beats remembering to add it.