Quick Answer: ISO 42001 is the international standard for AI management systems. It was published in December 2023. Certification proves an accredited third party has audited how your organization governs AI. It applies to any organization that builds, provides or uses AI systems. That includes companies deploying models built by someone else.
Your last three enterprise deals came with a security questionnaire. The newest version has a section that did not exist eighteen months ago.
It asks how you govern AI. Who approved the model. What happens when it produces a wrong answer. Whether anyone reviews training data. Procurement wants a document, not a paragraph about your values.
That is the pressure driving interest in ISO/IEC 42001:2023. No law compels it in the United States. Customers do.
Here we cover what the standard requires, who it applies to, and what certification takes. We also talk about the part the explainers skip: the operating work that follows the certificate.
The ISO 42001 standard builds an AI management system, abbreviated AIMS. Think of it as the governance layer sitting above every AI system you run.
It follows the same plan-do-check-act structure as ISO 27001 and ISO 9001. If you have run a management system before, the shape is familiar.
Clauses 4 through 10 define the system itself. Context and scope. Leadership and policy. Planning and risk. Support and competence. Operation. Performance evaluation. Improvement. These clauses are mandatory.
Annex A is different. It holds 38 AI-specific controls grouped under 9 control objectives, numbered A.2 through A.10. The objectives cover AI policy, internal organization, resources and impact assessment. They also cover the AI system lifecycle and data. The last three cover transparency, responsible use and third-party relationships.
Annex A is a reference set, not a checklist. Our ISO 42001 requirements checklist works through every control area with the evidence each expects. You choose which controls apply based on your risk and impact assessments. A Statement of Applicability records every inclusion and every exclusion, with justification.
Annex B gives implementation guidance for each control. It is informative rather than mandatory, but auditors read it. Annexes C and D add risk-source ideas and sector-specific notes.
Two companion standards matter here. ISO/IEC 42005:2025 covers AI system impact assessment. ISO/IEC 23894:2023 covers AI risk management guidance. Neither is certifiable on its own.
Three groups are being asked for it right now:
The pattern worth naming: AI vendors now get AI governance questions. They arrive in the same security review that asks for SOC 2. Two years ago that section was blank. Now it has weight in the scoring.
ISO 42001 compliance also matters for internal AI use. If your finance team runs a model that flags invoices, it sits inside the boundary. So do AI features that arrived inside SaaS tools nobody catalogued.
That last category is where scoping gets uncomfortable. Most organizations cannot name every AI system in use.
Short version: they do different jobs and share evidence.
ISO 27001 secures the data. ISO 42001 governs the decisions a model makes with that data. An encrypted training set can still produce a discriminatory output. ISO 27001 has nothing to say about that.
SOC 2 is an attestation against trust services criteria, not a certification against a standard. It covers security and availability. It does not cover model behavior, training data provenance, or explainability.
The NIST AI Risk Management Framework is the closest in subject matter. It is voluntary US guidance, published as NIST AI 100-1 in January 2023. It has four functions: Govern, Map, Measure and Manage. It produces no certificate, but our compliance practice helps if you are weighing several frameworks.
That distinction decides the answer for most buyers. If a customer asks for proof, only one of these gives you something to send.
Work overlaps more than the documents suggest. Your existing risk methodology, internal audit program and management review cadence carry across. If you already hold ISO 27001, the path to a second certification is shorter.
Certification is a two-stage audit performed by an accredited certification body, and our step-by-step certification roadmap walks the full sequence. ISO/IEC 42006:2025 sets the rules those bodies follow, including how audit time is calculated.
Here is what the full sequence produces.
|
Stage |
What you do |
What it produces |
|---|---|---|
|
Scope definition |
Decide which AI systems and business units sit inside the boundary |
A documented scope statement with justified exclusions |
|
AI system inventory |
Catalogue every AI system, including embedded SaaS features |
A maintained inventory with owners |
|
Risk and impact assessment |
Assess risk to the organization and impact on individuals and society |
Risk register and AI system impact assessment records |
|
Control selection |
Choose applicable Annex A controls and justify exclusions |
Statement of Applicability |
|
Implementation |
Build policy, lifecycle controls, data governance and monitoring |
Operating controls with evidence |
|
Internal audit |
Audit your own system against the standard |
Internal audit report and findings |
|
Management review |
Leadership reviews performance and resourcing |
Documented review with decisions |
|
Stage 1 audit |
Certification body reviews documentation |
Readiness findings, gaps to close |
|
Stage 2 audit |
Certification body tests implementation |
Certificate, or nonconformities to fix |
Two things surprise teams here:
After certification, the cycle continues. Surveillance audits run annually. Recertification follows on a three-year cadence.
Most ISO 42001 AI management system projects do not fail at the audit. They stop months earlier, and always in the same places.
The inventory is the first casualty. Teams list the models they built. They miss AI features that arrived inside tools they already pay for. A note-taker, a support triage bot, a resume screener in the recruiting platform. Nobody catalogued them because nobody bought them as AI.
Then ownership blurs. Model risk sits between engineering, legal, product and security. The gap assessment gets completed. It names twenty gaps. It names no owner for any of them.
Impact assessments get treated as a document rather than a process. Somebody writes one, files it, and moves on. Then the model gets retrained and the behavior changes. The assessment now describes a system that no longer exists.
Monitoring is where audits actually fail. The standard expects continuous operation. The auditor asks for six months of evidence that somebody watched model behavior. Most teams can produce a policy saying they would. They cannot produce the logs.
The staffing math is the honest part. Running an AIMS is a fraction of a role, forever. It is not a project with an end date. The median US wage for an information security analyst was $124,910 in May 2024. AI governance skills sit above that. Hiring for it takes months you do not have.
If you run on Microsoft, much of the evidence layer already exists. It is usually just not configured or retained:
Many vendors here explain the standard, then sell a course or an audit. BEMO does the implementation.
We own the AI system inventory rather than asking you to produce one. We run the risk and impact assessments. We write the Statement of Applicability that an auditor will accept.
We also configure the Microsoft surfaces that produce your evidence: Purview policies, conditional access, log retention, and Foundry evaluations wired to run on a schedule.
Then we operate it. Monitoring output gets collected. Impact assessments get repeated when models change. Internal audit runs before the certification body arrives.
BEMO stays through Stage 2 and past it, because surveillance audits are part of the engagement rather than a handoff. That is how the AI compliance work is structured, and the wider AI managed services sit alongside it.
The AI governance section of a security review is not going away. It is getting longer.
Right now most vendors answer it with a paragraph about responsible AI principles. That is a paragraph competing against a certificate.
An AI management system takes months to build and staff you probably do not have. It also takes continuous operation once it exists. That is the part catching teams out.
BEMO builds it, runs it, and owns the outcome through the audit. Book a gap assessment to see where your AI systems stand today.
No US law requires ISO 42001 today. The pressure is commercial. Enterprise customers, procurement teams and partners increasingly ask for AI governance evidence. This is the only certifiable answer available.
Most organizations should plan for several months from gap assessment to certificate. Teams with a mature ISO 27001 system move faster. Risk processes and audit habits already exist. Starting cold with no AI inventory takes considerably longer.
Yes. The standard applies to organizations that provide or use AI systems. Building them is not required. Your controls focus on supplier assessment, use governance and monitoring rather than model development.
No. ISO/IEC 27001:2022 has 93 controls across 4 themes, all focused on information security. It does not address model behavior, training data provenance, explainability or impact on affected individuals.
An accredited certification body. ISO/IEC 42006:2025 sets the competence and audit-time requirements those bodies must meet. Confirm current accreditation status directly with any body you shortlist.