ISO 42001 & AI Governance

Establish responsible AI governance and an artificial intelligence management system aligned to ISO/IEC 42001:2023.

Support
AI system inventory
Risk and impact assessment
Responsible AI governance
Continual improvement

AI Governance Must Cover How AI Is Selected, Used and Reviewed

ISO/IEC 42001 provides requirements for establishing, implementing, maintaining and continually improving an artificial intelligence management system. ITFR helps organisations understand their AI systems, assign accountability, assess risk and opportunity, and establish practical governance around responsible use.

AI context and scope
Define the organisation, AI services, providers, users and activities covered by the management system.

AI system inventory
Record approved AI systems, use cases, owners, data dependencies and relevant third parties.

Roles and accountability
Establish leadership oversight, responsibilities, approvals and operational ownership.

AI risk and impact assessment
Assess security, privacy, reliability, transparency, human and business impacts.

AI lifecycle controls
Manage selection, development, deployment, use, monitoring, change and retirement.

Performance and improvement
Review objectives, incidents, metrics, internal findings and corrective actions.

The result: a structured AI management system with clearer ownership, risk decisions, approved use and evidence of responsible oversight.

Benefits at a glance

Responsible AI Use

Connect innovation with defined accountability, acceptable use and review.

Clearer AI Risk Decisions

Assess risk and impact across AI systems, data, people and third parties.

Improved Trust

Support transparency, traceability, reliability and stakeholder confidence.

Continual Governance

Review AI systems and controls as technology, use and risk change.
GOVERN IT · ISO 42001 & AI GOVERNANCE

Choose the Right AI Governance Engagement

Choose a readiness assessment to establish your current position or implementation support to build an AI management system and supporting evidence.

AI Governance Readiness Assessment

Current State Review

against ISO/IEC 42001:2023

Understand AI governance gaps and priority actions

For organisations using or planning AI that need a clear view of systems, accountability, risk and management-system readiness.

Scope & Context Review
Confirm organisational boundaries, AI activities, providers and interested parties.

AI System Inventory
Identify approved and known AI systems, use cases, owners and data dependencies.

Governance & Accountability Review
Assess leadership, policies, roles, approvals and reporting.

AI Risk & Impact Review
Sample how AI risk, opportunity and impact are identified and treated.

Evidence & Control Review
Review available policies, records, monitoring and operational evidence.

Prioritised Readiness Roadmap
Define actions, owners, dependencies and suggested sequencing.

 

BEST FOR

Organisations that need an evidence-led AI governance baseline before broader adoption or formal implementation.

ISO 42001 Implementation Support

Guided AIMS Program

against ISO/IEC 42001:2023

Governance, controls and evidence preparation

For organisations that want structured help establishing or improving an AI management system and preparing for independent assurance.

Everything in the Readiness Assessment
Scope, inventory, governance, risk, evidence and roadmap.

AI Policy & Governance Design
Develop practical objectives, responsibilities, acceptable use and oversight.

Risk & Impact Assessment Process
Create repeatable methods for AI risk, impact and treatment decisions.

AI Lifecycle Controls
Define selection, approval, deployment, monitoring, change and retirement controls.

Supplier & Data Governance
Address AI providers, contracts, data sources, access and relevant dependencies.

Performance Review & Improvement
Establish monitoring, incidents, internal review and corrective action.

Assurance Readiness Support
Organise evidence and prepare teams for the selected independent assessment pathway.

BEST FOR

Organisations that need coordinated AI management-system implementation rather than an isolated acceptable-use policy.

One Management System, Different AI Use Cases

A public generative AI assistant, Microsoft Copilot and a business-critical automated decision system do not create identical risks.

ITFR can apply common governance with proportionate assessment and controls for each use case.

You maintain consistent accountability without treating every AI system as equally complex or harmful.

AI GOVERNANCE EXPERTISE

Not Sure Which AI Systems Are Already in Use?

ITFR can help establish an inventory, identify business owners and define an initial governance and risk workstream.

1

AI System Discovery

Identify approved and known AI services, use cases, owners and providers.

2

AI Risk & Impact Assessment

Assess business, data, security, privacy, reliability and human impacts.

3

Policy & Accountability

Define acceptable use, approval, responsibility, reporting and escalation.

4

ISO 42001 Readiness

Assess and improve the management system against ISO/IEC 42001:2023.

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Scale AI governance to the systems, use cases and impacts in scope.

Choose readiness or implementation support according to AI adoption, internal capacity and assurance goals.