AI Governance & Regulation: EU AI Act, NIST AI RMF, and What Engineers Must Produce
AI is now governed like buildings: rules sorted by risk (a garden shed needs no permit; a school needs many), plus inspectors who only accept paperwork. This topic maps the 2024-2026 regimes — the EU AI Act's risk tiers and dates, NIST AI RMF and its Generative AI Profile, the US state patchwork, China, the UK, ISO/IEC 42001 — and then gets concrete about the exact artefacts a platform team must ship to be defensible.
01.The Problem: "Trust Us" Is Not an Engineering Artefact
Your team swaps the underlying model on a Tuesday. Nobody reviews anything; the metrics dashboard looks fine; customers notice three weeks later that the HR-screening feature started down-ranking candidates with non-English names.
Now a customer's lawyers, or an EU regulator, ask you questions like:
- What is this system for, exactly?
- What data built it, and did you examine it for bias?
- What did your evaluations show, per population?
- When it fails, how do you know — and who was in charge?
"Trust us, we tested it in staging" is not an answer any of those people can audit. Governance is the discipline of making the answers artefacts: documents, logs, evaluation dossiers and registers that exist before the question.
AI governance = rules about what you must be able to prove, plus the paperwork that proves it.
And the rules are no longer hypothetical. Between 2024 and 2026 the EU passed a full law, the US assembled a framework-plus-state-patchwork, China shipped operational rules for generative services, and certifiable management-system standards (ISO/IEC 42001) arrived. This topic is the map — and the concrete deliverable list a platform team has to ship.
Regulatory Map → Required Engineering Artefacts 🗺️
Regulatory Map → Required Engineering Artefacts 🗺️
Major regimes classify AI by risk and duty, then ask for the same evidence set: documentation, data governance, evaluations, logs, human oversight, and an owned risk register.
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