ISO 42001 (AI): A Simple Playbook to Get Audit-Ready

ISO 42001 introduces a management system for Artificial Intelligence — the AI Management System (AIMS). It sets out how organisations govern AI responsibly across people, processes, data, and technology.

Unlike technical standards, ISO 42001 focuses on how you manage AI risk, ethics, transparency, and accountability. It’s the missing framework between fast-moving AI innovation and enterprise-grade assurance.

This playbook shows how to become audit-ready in weeks using Microsoft 365, SharePoint, Power Automate, and Teams — without needing new platforms or expensive tooling.

1️⃣ Build a Living AI Model Inventory

The cornerstone of any AIMS is a complete and versioned record of every AI system in use — whether built, bought, or piloted internally.

Capture key details: model name, purpose, owner, data sources, and deployment surface (e.g. app, chatbot, workflow).
Classify model type: Large Language Model (LLM), classical ML, statistical model, or hybrid.
Track risk categories: safety, bias, privacy, security, and legal/compliance exposure.
Document controls: content filters, prompt guardrails, evaluation outcomes, red-team results, retraining cadence.
Log lifecycle events: approvals, major changes, retirements, and retraining.

💡 Tip: Store the model register in SharePoint or a Power Apps form. Enable version history and export to PDF monthly for audit evidence.

2️⃣ Right-Size the AI Risk Process

An AIMS doesn’t need a complex data-science risk model. Focus on structured, explainable, and repeatable decision-making.

Risk Category	Example Threats	Typical Controls
Data Security	Prompt injection, leakage of training data, cross-tenant exposure	Retrieval isolation, network segmentation, masked inputs, rate-limits
Bias & Fairness	Under-represented data, biased training labels	Diverse datasets, peer review, counterfactual testing
Reliability	Hallucination, unapproved self-learning	Evaluation datasets, retrieval grounding, human-in-loop verification
Legal & Ethical	Copyright, explainability, discrimination, misinformation	Transparency logs, use policies, opt-out mechanisms, red-team testing

✅ Outcome: Each model has a visible, reviewed risk profile and mitigation record — easily exportable as audit evidence.

3️⃣ Embed Human Oversight and Accountability

Human-in-the-loop isn’t optional. ISO 42001 requires evidence that critical AI decisions are reviewed and approved by humans.

Define which outputs require approval — e.g., financial recommendations, safety-related actions, or customer-facing messages.
Use Microsoft Teams Approvals or Power Automate to log sign-offs.
Archive approved outputs and reviewer notes in SharePoint with timestamps.
Document when exceptions are allowed (e.g., low-impact automation).

🧭 Goal: Demonstrate that every AI outcome with potential harm has an accountable human checkpoint before release.

4️⃣ Operational Monitoring and Incident Response

AI governance is continuous. Build lightweight monitoring that links to your existing SOC or DevOps rhythm.

Usage monitoring: Capture queries, context, and volumes to identify drift or misuse.
Performance drift: Compare accuracy or bias metrics to baseline values.
Incident management: Route harmful or unsafe outputs through your existing security incident process.
Rollback/disable: Define a rapid disable or model rollback procedure and test it quarterly.
Periodic evaluation: Review model risk classification every six months or after major retraining.

Key metrics to track:

Number of models under active governance
Drift detection events resolved within SLA
Percentage of models with bias testing evidence
Number of AI incidents logged and resolved

5️⃣ Automate Evidence Using Microsoft 365

Evidence doesn’t need to be manual. Most AIMS artefacts can be generated automatically from Microsoft 365 and Azure tools.

Power Automate: Schedule monthly exports of model inventories, evaluations, and approvals into SharePoint.
SharePoint: Use retention policies and versioning to maintain artefacts across audits.
Purview: Apply sensitivity and retention labels to AI artefacts for controlled access and regulatory alignment.
Entra ID: Produce quarterly access-review reports to prove principle-of-least-privilege enforcement.
Defender for Cloud Apps: Alert on non-approved AI or API usage across the tenant.

✅ Result: An auditable, lightweight AIMS that captures policy, evidence, and lifecycle records automatically.

6️⃣ Communicate Transparency and Trust

Transparency isn’t just an ethical requirement — it’s a trust driver. ISO 42001 expects evidence of how AI decisions are explained and communicated.

Explainability statements: Publish a clear overview of each model’s purpose, limitations, and data handling.
Stakeholder communication: Use your intranet or Compliance Hub to publish policy updates and approved use-cases.
Training & awareness: Deliver short modules explaining responsible AI, bias, and ethical review workflows.
Public disclosure: For high-impact AI, include contact details and escalation procedures for external feedback.

💬 Tip: Transparency doesn’t require code explainability — it’s about showing intent, control, and accountability.

7️⃣ The Path to Certification

ISO 42001 certification follows the same structure as ISO 27001 — Plan, Do, Check, Act — but focuses on AI-specific risk.

Typical roadmap:

Weeks 1–2: Define AI policy, roles, and governance committee
Weeks 3–6: Build model inventory and risk register
Weeks 7–10: Implement oversight, monitoring, and evidence automation
Weeks 11–12: Conduct readiness audit and finalise AIMS documentation

Most organisations can achieve ISO 42001 readiness within three months when leveraging their existing Microsoft 365 and Azure foundations.

Why This Matters

Board confidence: Demonstrates structured governance of AI innovation.
Customer assurance: Answers procurement questionnaires with evidence-ready artefacts.
Regulatory readiness: Positions you for future compliance with EU AI Act and Australian AI principles.
Operational efficiency: Turns governance from reactive paperwork into continuous automation.

🎯 Bottom line: ISO 42001 is not a technical audit — it’s a trust framework. The faster you integrate it into daily workflows, the easier certification and stakeholder confidence become.

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