Preparing for an ISO 42001 audit can feel overwhelming — not because the ideas are complicated, but because governing AI touches every part of an organisation. AI systems sit in product, engineering, data, risk, security, HR, and even the supply chain.

And as many organisations are realising, the audit process expects a level of structure that most AI initiatives simply weren’t built with.

That’s why a good ISO 42001 checklist matters.

It gives you a way to step back, assess where you are, run a realistic gap analysis, and define a clear approach for managing AI responsibly. This blog covers the essentials at a high level — and you can download the full readiness checklist for a more structured way to prepare.

Why ISO 42001 Requires More Structure Than You Think

ISO 42001 is the world’s first AI management system standard, created by ISO and the International Electrotechnical Commission (IEC) to bring clarity, accountability, and consistency to AI governance. It builds on ideas found in other frameworks and ISO standards, but focuses specifically on the unique risks of AI technology — things like fairness, transparency, explainability, misuse, and data quality.

A few expectations are worth calling out early:

Documentation of AI decision-making processes is necessary to ensure transparency and accountability.
Human oversight is essential, especially in high-risk scenarios such as credit scoring, healthcare diagnostics, or automated approvals.
Organisations of any size, type, and nature involved in developing, providing, or using AI-based products or services fall within ISO 42001’s scope.
Responsible AI isn’t optional anymore — between the ISO standard, the EU AI Act, and existing frameworks, the pressure to ensure ethical AI practices is only increasing.

ISO 42001 helps organisations build trust, manage risks, ensure compliance, and demonstrate the responsible use of artificial intelligence — which, as many teams are discovering, is quickly becoming a competitive advantage.

What Auditors Typically Look For in ISO 42001

At a high level, an ISO 42001 checklist focuses on core areas like governance, leadership, risk management, data protection, transparency, AI system lifecycle controls, and continuous improvement.

The downloadable version breaks this into simple steps, but the themes are consistent across the standard:

1. Define Your AIMS Scope & Context

The first step in preparing for ISO 42001 compliance is getting management support and clearly defining the AIMS scope.

That means understanding:

what AI systems exist
where they sit in the organisation
how they support AI objectives
what internal and external factors shape your environment

This is where you map stakeholders, decision makers, AI initiatives, and the real-world context your AI operates in. It’s also where you start to uncover AI-specific risks and unique risks tied to your organisation.

This foundation influences everything else — governance, risk management, documentation, and system lifecycle controls.

2. Build Your AI Governance Structure

Governing AI effectively requires clarity around:

roles and responsibilities
escalation paths
human oversight
policies for ethical use
guidelines for responsible innovation
how AI fits within your wider management system

Many organisations underestimate how much governance auditors expect. Even at a high level, you need documented AI policy, leadership involvement, and a clear structure for ensuring ethical AI practices. If you already manage other frameworks (ISO 27001, ISO 9001, SOC 2, NIST), some of this will feel familiar — but AI introduces challenges those standards never addressed.

3. Run a Meaningful AI Risk Assessment

ISO 42001 places heavy emphasis on AI risk.

Your audit process must show that you:

identify AI-specific risks
assess impacts and likelihood
understand data-related issues
manage risks through mitigation and controls
run risk assessments consistently across AI systems
consider fairness, transparency, and societal impact

An effective gap analysis should compare current AI practices against ISO 42001 requirements to identify areas for improvement — not just compliance gaps, but operational ones. This includes risks across data, models, human oversight, misuse, security, and system lifecycle changes.

For organisations already working with risk management frameworks, this step fits naturally into existing processes. For AI-heavy teams, this is often where the real work begins.

4. Strengthen Documentation Across the AI Lifecycle

ISO 42001 expects clear, centralised, accessible documentation across the full system lifecycle. At minimum, you’ll need evidence covering:

design decisions
development processes
model testing and validation
deployment approvals
AI system impact assessments
data quality controls
transparency and explanation requirements
controls for responsible use
change management
real-time monitoring
how incidents are tracked

Creating, reviewing, and updating a centralised repository for ISO 42001-related documents is necessary to ensure ongoing compliance — and it makes management review and internal audit far easier.

This is also where you’ll feel the benefit of an artificial intelligence management system (AIMS) rather than ad-hoc documents scattered across teams.

5. Implement Controls & Human Oversight

This is where governance becomes real.

You need controls in place for:

data management
model development
fairness and transparency
human review in high-risk decisions
managing AI within supply chain management
ensuring ethical and responsible use
monitoring performance
logging and corrective actions

Controls don’t need to be complex, but they must be practical and consistently applied. This is particularly important for organisations using AI in decision making or customer-facing scenarios.

6. Monitor, Review & Improve the AIMS

Like any ISO management system, ISO 42001 expects continual improvement. Auditors want to see:

real-time monitoring
internal audits
management review
track-and-resolve processes
corrective actions
system updates based on new risks, data, or behaviours
evidence that the AIMS is working, not just written down

This is where ISO 42001 aligns closely with quality management standards — the expectation that you don’t just set controls once, but adapt them over time as your AI evolves.

Why a Checklist Helps (Even at a High Level)

A readiness checklist doesn’t replace the standard, and it doesn’t replace implementation guidance, but it does help you:

break the ISO 42001 requirements into manageable steps
compare your current posture to the standard
run a realistic gap analysis
understand the audit process
define responsibilities
avoid missing key evidence
align teams across AI, security, HR, engineering, and compliance
prepare for certification without guesswork

It’s simply a structured way to manage complexity — and complexity is something AI has plenty of.

What’s Included in the Downloadable Checklist

Without giving anything away, the PDF checklist includes:

clear preparation areas
high-level categories aligned to the standard
prompts for documentation
references to governance, risk, lifecycle controls, and improvement
space to track progress
a straightforward, practical tool that helps you get organised

It’s designed for teams who want to understand what good looks like, without drowning in detail too early.

How Hicomply Helps Organisations Preparing for ISO 42001

The checklist gives you structure.

Hicomply helps you operationalise it.

Our platform supports:

documentation management
AI system inventories
risk assessments
internal audit workflows
real-time monitoring
controls and corrective actions
management review
versioning and approvals
integration with other frameworks
audit-ready reporting

It brings your entire artificial intelligence management system into one place — so you’re not chasing evidence, rewriting policies, or guessing whether you’re audit-ready.