ISO 27001 and ISO 42001: Creating a Practical Roadmap for AI Governance

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Artificial intelligence is becoming part of business operations across industries. Organizations use AI to automate processes, develop software, analyze information, and improve customer experiences. As adoption grows, businesses need a structured way to manage information security alongside the risks associated with AI systems.

ISO/IEC 27001 and ISO/IEC 42001 can help organizations establish this foundation. Although the two standards address different management objectives, their processes can be coordinated to support a more consistent approach to governance.

Understanding how they fit together can help businesses plan their implementation efforts without unnecessarily duplicating existing work.

Understanding ISO 27001 and ISO 42001

ISO/IEC 27001:2022 specifies requirements for an Information Security Management System (ISMS). It provides a framework for identifying information security risks, implementing appropriate controls, and continually improving security practices.

ISO/IEC 42001:2023 specifies requirements for an Artificial Intelligence Management System (AIMS). It helps organizations establish processes for managing AI-related risks and opportunities.

The distinction is important. Information security management focuses on protecting information and information assets, while AI management addresses broader considerations associated with developing, providing, or using AI systems.

An organization may have established security controls but still need additional procedures for AI risk assessment, impact assessment, and lifecycle oversight.

Why Businesses Should Consider Both Standards

Consider a software company that uses AI to analyze customer requests and generate automated responses.

Its existing security programme might include access controls, secure infrastructure, supplier reviews, and incident response procedures. These practices help protect information and systems.

However, the company may also need to consider the intended purpose of the AI application, the potential consequences of inaccurate outputs, the need for human review, and the processes used to monitor performance.

These additional questions illustrate why information security and AI governance should be considered together without treating them as identical.

Four Steps Toward a Coordinated Management System

1. Review Existing Security Processes

Organizations that already operate an ISMS should begin by reviewing its scope, risk assessments, policies, supplier management, and audit procedures.

Some processes may be suitable for reuse within an AI management system. Others may require changes to address AI-specific requirements.

The goal is to identify existing capabilities before creating additional procedures.

2. Identify AI Systems and Responsibilities

Create an overview of the AI systems the organization develops, provides, or uses.

For each relevant system, identify its intended purpose, business owner, technical dependencies, and governance responsibilities. Determine which teams are responsible for assessing risks, approving changes, and monitoring issues.

This information gives the organization a clearer view of its AI activities and the processes needed to oversee them.

3. Assess Risks and Identify Gaps

Review whether existing risk-management practices address the requirements of ISO 42001.

Information security assessments remain important, but AI governance may require additional consideration of system impacts, intended use, and other risks relevant to the application.

Document the gaps between existing processes and the applicable requirements. Assign priorities based on the organization's context, risk exposure, and implementation needs.

4. Establish Evidence and Review Processes

A management system needs records that demonstrate how activities are performed and decisions are made.

Organizations should establish suitable processes for maintaining risk assessments, approvals, monitoring records, audit findings, and corrective actions.

Where a record supports multiple requirements, it may be referenced across both systems. However, the organization should ensure that each applicable requirement has adequate supporting evidence.

Regular reviews help keep these records current as AI systems and business needs change.

Connecting Governance With Regulatory Responsibilities

For organizations operating in Europe, management-system standards should be considered alongside applicable legal requirements, including those under the EU AI Act.

The Act's requirements depend on factors such as an organization's role and the AI system's intended purpose and classification.

ISO 27001 and ISO 42001 can support relevant governance activities, but neither certification automatically establishes compliance with every applicable EU AI Act obligation.

Businesses should assess their legal responsibilities separately and determine how their management systems can support the required processes, documentation, and oversight.

Making AI Compliance Easier to Manage

As the number of AI systems grows, organizations may find it difficult to maintain accurate inventories, assessments, documentation, and approval records across separate tools.

A centralized governance process can help teams understand which systems they manage, which risks have been assessed, and which actions remain outstanding.

AI compliance software can support this work by connecting system inventories, risk classifications, documentation, and evidence management. The appropriate solution depends on the organization's operational needs and applicable requirements.

For additional guidance, read the ISO 27001 and ISO 42001 integration guide. It explores how organizations can approach the two standards as complementary parts of their governance framework.

Conclusion

ISO 27001 and ISO 42001 address different but complementary management challenges. By reviewing existing capabilities, identifying AI-specific requirements, and coordinating suitable processes, organizations can develop a more structured approach to information security and AI governance.

The objective is not simply to pursue two certifications. It is to establish responsibilities, maintain reliable evidence, and create processes that can adapt as technology and risks evolve.

A practical roadmap helps organizations move from fragmented governance activities toward a management system that supports their actual operations.

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