An AIMS (AI Management System) is the set of policies, processes, roles and controls an organization uses to govern AI responsibly across its lifecycle. It is defined by ISO/IEC 42001:2023, the first certifiable international standard for AI management, and does for AI what ISO 27001 does for information security.

What is included in an ISO 42001 AIMS?

A scope and AI policy, an AI risk assessment and AI system impact assessment, a governed inventory of AI systems with risk tiers and model cards, Annex A operational controls (data governance, human oversight, security, supplier management), a Statement of Applicability, and continuous monitoring, internal audit and management review.

How do I start building an AIMS?

Define scope, run an AI risk and impact assessment, adopt AI policies, inventory and risk-tier your AI systems, implement Annex A controls, write the Statement of Applicability, and monitor continuously. A concrete first control is governing AI data egress — redacting secrets before they reach public LLMs and logging the evidence.

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AI Governance

What Is an AIMS? The ISO 42001 AI Management System, Explained

July 1, 2026 · 7 min read

Everyone says “stand up an AIMS” — but what is it, actually? Here’s the AI Management System in plain terms, and the first control worth putting in force.

An AIMS — AI Management System — is the set of policies, processes, roles and controls an organization uses to govern its AI responsibly across the whole lifecycle. It is defined by ISO/IEC 42001:2023, the first certifiable international standard for AI management. If you already know ISO 27001, the shape is familiar: 42001 does for artificial intelligence what 27001 does for information security.

Why an AIMS matters now

Regulators and customers have stopped taking “we use AI responsibly” on faith. The EU AI Act imposes concrete obligations on high-risk systems; the NIST AI RMF sets expectations for measuring and managing AI risk; and enterprise buyers increasingly ask for AI governance in security questionnaires. An AIMS is the structure that lets you answer all three consistently instead of reinventing an answer per request.

What’s inside an AIMS

ISO 42001 pairs management-system clauses (4–10) with a set of AI-specific Annex A controls. In practice a working AIMS contains:

Scope and context — which AI systems and uses the AIMS covers, and the internal/external issues around them.
Leadership and an AI policy — top-management commitment and a signed policy for responsible AI use.
AI risk assessment and treatment — plus an AI system impact assessment for affected individuals.
A governed inventory of AI systems — each with a risk tier and a model card.
Operational controls — data governance, human oversight, security, and third-party/supplier management (Annex A).
A Statement of Applicability (SoA) — every Annex A control marked applicable or excluded, with justification.
Performance evaluation — continuous monitoring, internal audit, and management review.

AIMS vs ISMS: how ISO 42001 relates to ISO 27001

An ISMS (ISO 27001) protects the confidentiality, integrity and availability of information. An AIMS (ISO 42001) governs the responsible development and use of AI — fairness, transparency, human oversight, and data governance for AI systems. They share the same management-system backbone, so if you already run an ISO 27001 program, much of the machinery (risk process, internal audit, management review) carries straight over. Many controls cross-map, so evidence collected once can satisfy both.

How to stand up an AIMS

The path mirrors any management system: define scope, run an AI risk and impact assessment, adopt policies, inventory and risk-tier your AI systems, implement Annex A controls, write the SoA, and monitor continuously. Doing it in spreadsheets is where teams stall. The ISO 42001 platform in CATAAM scaffolds the full AIMS — clauses, Annex A controls, and a policy library — and validates each control with a native test, so you reach audit-ready in weeks rather than quarters.

The first control worth putting in force

You do not have to boil the ocean on day one. A concrete, high-value first control is governing AI data egress — stopping secrets and PII from reaching public LLMs, and logging it. Prompt Guard is a free, open-source way to enforce it: it redacts secrets before a prompt leaves the machine and emits evidence that latches directly into your AIMS. It is the fastest way to turn one Annex A control from a policy statement into a passing, logged control — and to see how shadow AI actually gets contained.

Stand up your ISO 42001 AIMS

See the ISO 42001 platform →

Frequently asked questions

What is an AIMS?: An AIMS (AI Management System) is the set of policies, processes, roles and controls an organization uses to govern AI responsibly across its lifecycle. It is defined by ISO/IEC 42001:2023, the first certifiable international standard for AI management, and does for AI what ISO 27001 does for information security.
What is the difference between an AIMS and an ISMS?: An ISMS (ISO 27001) protects information confidentiality, integrity and availability. An AIMS (ISO 42001) governs the responsible development and use of AI — fairness, transparency, human oversight and AI data governance. They share the same management-system structure, and many controls cross-map so evidence can satisfy both.
What is included in an ISO 42001 AIMS?: A scope and AI policy, an AI risk assessment and AI system impact assessment, a governed inventory of AI systems with risk tiers and model cards, Annex A operational controls (data governance, human oversight, security, supplier management), a Statement of Applicability, and continuous monitoring, internal audit and management review.
How do I start building an AIMS?: Define scope, run an AI risk and impact assessment, adopt AI policies, inventory and risk-tier your AI systems, implement Annex A controls, write the Statement of Applicability, and monitor continuously. A concrete first control is governing AI data egress — redacting secrets before they reach public LLMs and logging the evidence.