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AI governance & policy checklist

EU AI Act, NIST AI RMF, SOC 2, and internal-policy must-haves for shipping AI responsibly.

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Frequently asked questions

1.Is this EU AI Act compliant?

It covers the minimum for limited and minimal-risk AI systems in the EU. High-risk systems (Annex III: HR screening, credit, critical infra) require formal conformity assessment, CE marking, and post-market monitoring β€” this checklist is a starting point, not the full lift.

2.Which framework should I target first β€” NIST, ISO 42001, or SOC 2?

Start with NIST AI RMF (free, de facto US standard). Add SOC 2 Type II AI addendum if you're selling to enterprise. Pursue ISO 42001 certification if contract-required.

3.Do we need a dedicated AI lawyer?

For a small startup, no β€” general counsel with an AI briefing is enough. For anything touching healthcare, finance, HR screening, or employment law in the EU, yes.

4.What's the deadline pressure?

EU AI Act high-risk systems face August 2026 compliance. GDPR DPIA requirements apply now. NIST AI RMF is voluntary but de facto standard for federal contracts.

5.How does governance help revenue?

Enterprise buyers ask AI-governance questions in the first security questionnaire. Having documented answers turns a 6-week review into 1 week. It's a growth lever, not a cost.

AI governance in 2026: what every org actually needs

The EU AI Act is in force. The US NIST AI Risk Management Framework is the de facto standard for federal contracts. SOC 2 Type II now requires a documented AI posture. This checklist is the minimum β€” 16 items across policy, risk, operational controls, and people β€” that an org with 50+ employees shipping AI in production should have.

Four pillars

Policy & scope

A written acceptable-use policy. An approved-tool inventory. An exception path (because people will experiment regardless β€” give them a safe lane). A public-facing AI-use disclosure if your regulator requires one. These four items together catch 80% of the "someone leaked data to ChatGPT" failure modes.

Risk management (NIST AI RMF)

A risk register with classification (prohibited / high / limited / minimal per EU AI Act), DPIAs for AI touching personal data, a model card per deployed system, and a quarterly red-team review of high-risk systems. The classification step is load-bearing β€” it tells you which items need formal DPIAs versus lighter review.

Operational controls

SSO and MFA on every AI tool (consumer accounts banned for work data). Audit logs retained 12+ months. Data-loss prevention on AI inputs. Vendor security reviews (SOC 2 Type II, DPA, sub-processor list, incident disclosure SLA). A named incident-response playbook for AI incidents.

People & training

Annual AI-literacy training for all staff (30-60 min). Specialized training for engineers and data teams (prompt injection, eval, caching, routing). Code-of-conduct addendum on AI-generated content (disclosure in client work, copyright, academic integrity for edtech).

Frameworks to align with

  • EU AI Act: Risk classification + conformity assessment for high-risk systems.
  • NIST AI RMF: Govern / Map / Measure / Manage lifecycle. De facto US standard.
  • ISO/IEC 42001: AI management system standard. Pairs with ISO 27001 if you already have it.
  • SOC 2 Type II AI addendum: AICPA added AI criteria in 2025. Auditors now ask.
  • OWASP LLM Top 10: Technical security baseline for LLM apps.

Start small, mature over 12 months

A small startup doesn't need ISO 42001 certification in month one. It needs a written AUP, an approved-tool list, DPAs with Anthropic/OpenAI/Google, and an incident playbook. Work up from there. Enterprise can target ISO 42001 over 12-18 months using this checklist as a gap analysis.

Governance is a revenue enabler

Enterprise buyers in 2026 ask AI-governance questions in the first security questionnaire. Not having answers costs deals. Having a documented AUP, DPAs, and a model registry turns a 6-week security review into a 1-week review. That's a growth lever, not a cost.

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