The answer is… 42 (extended version)

(And no, we’re not joking. It’s also the number of the newest ISO standard for responsible AI: ISO/IEC 42001.)

If you’ve ever wondered how to actually prove that your organization is using AI responsibly—or that your AI-enabled product meets regulatory, ethical, and customer expectations—ISO 42001 might just be your guidebook to the galaxy of trust, compliance, and sanity in this rapidly changing world.

This isn’t a theoretical model. ISO/IEC 42001 is a full management system standard—just like ISO 27001 for security or ISO 9001 for quality—designed to be auditable, certifiable, and operational. It answers a critical market need: Can we prove that we’ve done our AI governance homework?

With ISO 42001, you can.

Here’s how.

Step 1: Define the Scope — Your AI Universe

Before launching your AI spaceship, you need to map your galaxy:

External and internal issues: Market demands, regulatory complexity, societal impacts, and internal maturity all shape how your AI will be governed.
Interested parties: This includes customers, regulators, partners—and especially different categories of AI users, both internal and external.
Applicable requirements: Legal obligations (e.g. EU AI Act), customer demands, internal values.
Scope of the AI Management System (AIMS): What functions, roles, technologies, and use cases are covered?
Scope of certification: Which parts of your business will be externally audited?

This scope-setting exercise uncovers the true scale of effort and helps justify the budget and resource needs to your leadership team.

Step 2: Identify Risks and Opportunities — Strategic Framing for AIMS

This step is not about operational risk. Instead, it's about your organization’s strategic capacity to adopt ISO 42001 and run an AI Management System:

Will AIMS improve your compliance posture?
Will it enhance internal coordination or reduce duplication?
Could it open new markets by showcasing trustworthiness?

On the flip side:

Do you have the resources to support it?
Are there leadership or skills gaps?
Will new controls slow product development?

These questions guide capability planning, making sure you have the strategic fuel for the journey.

Step 3: Risk Assessment — The Real-World AI Impact Evaluation

Unlike Step 2, this is where you face the real operational risks of AI usage.

What risks do your AI systems cause?
To whom?
And who can cause risks to your AI system or its users?

This means looking at:

The risks posed BY AI products or users—e.g., biased algorithms, hallucinations in generative models, autonomous decision-making failures.
The risks posed TO users or stakeholders—e.g., privacy violations, unfair treatment, legal liability, or even social harm.

You’ll evaluate:

Impact severity
Likelihood
Detectability
Category of user (developer, decision-maker, end-user, impacted party)
Category of AI (assistive tool, decision-support system, autonomous agent, etc.)

This forms the heart of your AI governance program. It’s not generic—it’s about your systems, in your context, with your users.

Step 4: Statement of Applicability — Your Control Blueprint

Now that you've assessed the actual risks, choose your tools.

Select applicable controls from ISO 42001 Annex A to treat those risks.
Justify any exclusions in your Statement of Applicability (SoA).
Include both technical safeguards and organizational measures (like human oversight procedures or usage restrictions).

This SoA becomes a central governance artifact—and a key reference point for your external auditor.

Step 5: Internal Audit Program — Verifying the Mission

Build your internal audit process like a monitoring satellite:

Define which areas will be audited, by whom, and how often.
Auditors must be competent and impartial—no auditing your own code or system!
Establish how findings are documented, tracked, and closed.
Make sure auditees are trained to handle nonconformities without panic—and with clear timelines.

Step 6: Continuous Improvement — what if you only have OFIs from the internal audit?

You don’t need to fail to improve.

Even “Opportunities for Improvement” (OFIs) matter—but not all are worth implementing. Create an evaluation method based on:

Risk reduction
Cost-benefit
Stakeholder impact
Feasibility

Once implemented, measure effectiveness:
Did the risk drop? Did trust improve? Was a KPI moved?

Treat this like experimental design—data-driven, not reactive.

Step 7: Objectives, KPIs, and Management Review

This is where governance gets measurable.

Set SMART objectives for your AI governance.
Monitor KPIs like response time to incidents, accuracy improvements, reduced risk flags, audit closure rates.
Roll all this into your Management Review Meeting:
- Review objectives and risks
- Discuss audit results and SoA updates
- Plan resourcing, corrective actions, or strategic pivots

Document the minutes. Assign owners. Set deadlines.

Step 8: You’re Ready for Certification Audit

You’ve now:

Outlined scope and capability
Mapped real-world risks
Selected and justified controls
Audited your own system
Closed the loop on improvements
Set objectives and reviewed them

This isn’t just compliance—it’s competitive advantage.

So yes, the answer is 42.
Not just a nod to Douglas Adams—but a real standard that connects AI, ethics, governance, risk, and assurance into one measurable system.

ISO/IEC 42001 is your operational proof that you’re not just building AI—you’re building it responsibly.

NEW FEATURE! If you want to repost that my post and gain interest to YOUR social network page, here is the brief summary you can copy and paste to your own post with the link to my this post:

Implementing ISO 42001 — a $5,000 consultation in 3 pages article
Elena done the step-by-step breakdown of how to build an AI Management System (AIMS) that meets ISO/IEC 42001—the world’s first auditable AI governance standard.

✅ How to define your AIMS scope (users, systems, legal context)
✅ The difference between strategic risks vs. operational AI risks (yes, there are two types!)
✅ How to build your Statement of Applicability and select controls
✅ Setting up internal audits, nonconformity handling, and improvement cycles
✅ Defining SMART objectives, KPIs, and running a real Management Review
✅ What certification bodies actually look for—and how to be ready

Read the full breakdown here → bobkova.online/the-answer-is-42-extended-version/

📎 No filler. Just the real roadmap. Bookmark-worthy if you're: