Artificial intelligence is changing how organisations operate, make decisions, and manage business processes. From customer service and financial analysis to cybersecurity and recruitment, AI is becoming an important part of everyday operations.

However, introducing AI into business processes also creates risks involving data privacy, cybersecurity, accuracy, fairness, accountability, and regulatory compliance.

Organisations need clear governance structures to manage these challenges. They must understand where AI is being used, identify potential risks, establish appropriate controls, and demonstrate that their AI systems are managed responsibly.

Both international standards support responsible AI adoption, but they address different aspects of AI governance and risk management.

ISO 23894 provides guidance on managing AI-related risks, while ISO 42001 establishes requirements for an artificial intelligence management system.

Understanding the differences between these standards helps organisations determine how to use them together to strengthen governance, improve risk management, and support compliance readiness.

In this guide, we explain ISO 23894 vs ISO 42001, compare their objectives and requirements, explore certification differences, and provide practical guidance on implementing both standards.

What is the difference between ISO 23894 and ISO 42001?

The main difference between ISO 23894 and ISO 42001 is their purpose and application.

ISO/IEC 23894:2023 provides guidance for organisations that develop, produce, deploy, or use AI systems. It focuses on identifying, analysing, evaluating, treating, monitoring, and communicating risks associated with artificial intelligence.

ISO/IEC 42001:2023, on the other hand, specifies requirements for establishing, implementing, maintaining, and continually improving an Artificial Intelligence Management System (AIMS).

An AI management system provides the organisational structure needed to govern AI activities through policies, responsibilities, processes, objectives, and ongoing improvement.

In simple terms, ISO 23894 helps organisations understand how to manage AI risks, while ISO 42001 helps them establish a structured management system for governing AI.

These standards are complementary rather than competing approaches.

ISO 23894 vs ISO 42001: Quick comparison

Comparison	ISO/IEC 23894:2023	ISO/IEC 42001:2023
Official title	Information technology — Artificial intelligence — Guidance on risk management	Information technology — Artificial intelligence — Management system
Primary purpose	Guidance for managing AI-related risks	Requirements for an AI management system
Type of standard	Guidance standard	Requirements standard
Main focus	AI risk identification, analysis, evaluation, treatment, and monitoring	AI governance, management processes, accountability, and continual improvement
Certification	Not designed for standalone management-system certification	Supports third-party AIMS certification
Main audience	AI developers, providers, users, and risk management professionals	Organisations providing or using AI-based products or services
Risk management role	Provides detailed guidance on AI-related risk management	Requires organisations to establish and operate AI risk management processes
Organisational scope	AI risks within relevant organisational activities	Organisation-wide management system within a defined scope
Implementation approach	Adaptable risk management guidance	Structured management-system requirements
Relationship	Can support risk management activities within an AIMS	Can incorporate ISO 23894 guidance into its risk management processes

Organisations can use ISO 23894 independently to improve AI risk management practices or apply it alongside ISO 42001 to support a more comprehensive AI governance programme.

What is ISO 23894?

ISO/IEC 23894:2023 is an international standard that provides guidance on managing risks associated with artificial intelligence.

Published in February 2023 by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC), it helps organisations integrate AI risk management into existing business and governance activities.

The standard recognises that AI systems introduce risks that may differ from those associated with traditional information technologies.

These risks can involve uncertain outcomes, limitations in training data, biased decisions, unexpected system behaviour, and challenges related to transparency and accountability.

ISO 23894 provides a structured approach to considering these risks throughout the AI lifecycle.

What does ISO 23894 cover?

ISO 23894 addresses how organisations can apply risk management principles to AI systems and activities.

Its guidance supports several important activities.

Establishing the context of AI risks: Organisations should understand the purpose of an AI system, its operating environment, affected stakeholders, and potential consequences before conducting risk assessments.

Identifying AI-related risks: Teams should examine potential risks involving data quality, cybersecurity, privacy, reliability, fairness, operational performance, and other relevant factors.

Analysing and evaluating risks: Identified risks should be assessed using suitable criteria to determine their significance and whether treatment is necessary.

Treating AI risks: Organisations should select appropriate responses, which may include technical safeguards, human oversight, process changes, restrictions, or decisions not to proceed with certain AI applications.

Monitoring and reviewing risks: Risk management should continue as AI systems change, new information becomes available, or business conditions evolve.

ISO 23894 also encourages organisations to integrate these activities into their existing risk management practices rather than creating disconnected AI-specific processes.

Who should use ISO 23894?

ISO 23894 is relevant to organisations involved in developing, providing, deploying, or using AI technologies.

It can be particularly useful for AI developers, data science teams, cybersecurity professionals, enterprise risk managers, compliance officers, and business leaders responsible for AI adoption.

For example, a financial institution using AI to support credit assessments may apply ISO 23894 guidance to evaluate inaccurate predictions, fairness concerns, data protection risks, and operational dependencies.

The organisation can then document its findings, assign risk owners, and implement safeguards based on the significance of identified risks.

What is ISO 42001?

ISO/IEC 42001:2023 is an international standard that specifies requirements for an Artificial Intelligence Management System.

It was published in December 2023 to help organisations establish structured governance over the development, provision, and use of AI systems.

Unlike ISO 23894, which provides risk management guidance, ISO 42001 establishes management-system requirements that organisations can implement and have independently audited for certification.

The standard is designed to help organisations manage AI-related responsibilities through defined policies, leadership involvement, risk management, operational controls, performance evaluation, and continual improvement.

What does ISO 42001 cover?

ISO 42001 follows a management-system approach that connects AI governance with organisational objectives and responsibilities.

Its main areas include:

Organisational context: Understanding internal and external factors that affect AI governance, along with relevant stakeholder needs and expectations.

Leadership and accountability: Establishing AI policies, assigning responsibilities, and ensuring appropriate management oversight.

Planning and risk management: Identifying AI-related risks and opportunities, conducting AI system impact assessments, and planning suitable responses.

Resources and competence: Ensuring that employees have the knowledge, resources, awareness, and support needed to fulfil their AI governance responsibilities.

Operational controls: Implementing and managing processes required to develop, provide, and use AI systems responsibly.

Performance evaluation: Monitoring the management system, conducting internal audits, and reviewing its effectiveness.

Continual improvement: Addressing nonconformities, taking corrective action, and improving AI governance processes over time.

ISO 42001 also includes annexes that address AI control objectives, controls, implementation guidance, and additional organisational considerations.

Who should implement ISO 42001?

ISO 42001 is relevant to organisations that develop, provide, or use AI-based products and services, regardless of their size or industry.

It is especially useful for organisations seeking a formal AI governance structure or independent certification of their AI management system.

For example, a technology company developing AI applications for enterprise customers may implement ISO 42001 to establish consistent governance policies, risk assessment processes, internal controls, and management oversight.

This can help the company demonstrate that it has established an organised approach to managing AI responsibilities.

ISO 23894 vs ISO 42001: Seven key differences

Although both standards support responsible AI, several differences affect how organisations should approach implementation.

1. Purpose and objectives

ISO 23894 focuses specifically on AI risk management.

Its purpose is to guide organisations in understanding AI-related risks and applying suitable risk management practices throughout the AI lifecycle.

ISO 42001 has a broader management-system objective. It addresses the governance structures, responsibilities, processes, controls, and continual improvement activities needed to manage AI at an organisational level.

An organisation may therefore use ISO 23894 to strengthen its risk assessment methodology while relying on ISO 42001 to establish the wider governance framework.

2. Guidance vs management-system requirements

ISO 23894 is a guidance standard. It offers recommendations that organisations can adapt to their operating environment, risk profile, and business needs.

ISO 42001 contains management-system requirements that organisations must satisfy when seeking conformity with the standard.

This distinction is important because implementing selected ISO 23894 recommendations is not the same as meeting the requirements of ISO 42001.

Organisations seeking ISO 42001 certification must demonstrate that their management system meets the applicable requirements within its defined scope.

3. Risk management scope

ISO 23894 provides focused guidance on the risk management process for artificial intelligence.

It helps organisations consider AI-specific characteristics when identifying risks, evaluating potential consequences, selecting treatments, and reviewing outcomes.

ISO 42001 includes AI risk management as part of a broader management system.

It also addresses leadership, policies, organisational roles, operational planning, internal audits, management reviews, and continual improvement.

This means ISO 23894 can provide useful supporting guidance for risk management activities carried out under ISO 42001.

4. Certification requirements

One of the most important differences between ISO 23894 and ISO 42001 concerns certification.

ISO 23894 is not designed as a standalone certifiable management-system standard. Organisations can use its guidance to improve their practices, but there is no equivalent standalone ISO 23894 management-system certification under the standard itself.

ISO 42001, however, establishes requirements against which an organisation’s AI management system can be audited.

Organisations seeking certification should work with an appropriate certification body and understand the certification scope, audit process, and applicable requirements.

5. Governance and leadership responsibilities

ISO 23894 encourages organisations to integrate AI risk management into existing governance and decision-making processes.

It supports the involvement of relevant stakeholders and the assignment of appropriate risk management responsibilities.

ISO 42001 places more formal emphasis on management-system governance, including leadership commitment, policies, defined responsibilities, and management review.

This makes ISO 42001 particularly useful for organisations that need to establish consistent AI governance across multiple business units or departments.

6. Documentation and audit readiness

ISO 23894 supports documenting AI risk assessments, treatment decisions, monitoring activities, and relevant risk management information.

However, it does not establish the same management-system documentation and conformity assessment requirements as ISO 42001.

ISO 42001 requires organisations to maintain appropriate documented information and demonstrate that their AI management system operates effectively.

This includes evidence relating to policies, risk management activities, internal audits, management reviews, corrective actions, and other applicable processes.

For organisations seeking certification, reliable documentation and evidence management are particularly important.

7. Continual improvement and monitoring

Both standards recognise that AI risks can change over time.

ISO 23894 supports ongoing monitoring and review of AI-related risks as systems, data, and operating conditions evolve.

ISO 42001 includes continual improvement as a formal management-system requirement.

Organisations must evaluate the performance of their AI management system, address identified issues, and take appropriate action to improve its effectiveness.

Using both standards can help organisations connect ongoing AI risk reviews with broader management-system improvement activities.

Quick link: NIST AI RMF vs. ISO 42001 vs. EU AI Act

How ISO 23894 and ISO 42001 work together

ISO 23894 and ISO 42001 can be used together to create a more structured and practical approach to AI governance.

ISO 42001 provides the organisational management system, while ISO 23894 can help organisations develop and operate the AI risk management processes that support that system.

For example, ISO 42001 requires organisations to address AI-related risks within their management-system activities.

ISO 23894 provides supporting guidance that can help teams identify those risks, evaluate their significance, select appropriate treatments, and maintain ongoing oversight.

Example: Implementing both standards in a financial institution

Consider a financial institution introducing an AI-powered fraud detection system.

The organisation wants to improve its ability to identify suspicious transactions while ensuring that the system operates securely, reliably, and responsibly.

Under ISO 42001, the institution can establish governance responsibilities, define AI policies, document management-system processes, and introduce appropriate oversight.

Using ISO 23894, the institution can then develop a structured risk assessment process for the fraud detection system.

Activity	ISO 42001 contribution	ISO 23894 contribution
AI governance	Establishes management-system responsibilities and policies	Supports integration of AI risk management into governance
Risk identification	Requires relevant AI risk assessment processes	Guides identification of AI-related risks
Risk evaluation	Establishes organisational risk management requirements	Supports analysis and evaluation of AI risks
Risk treatment	Requires appropriate risk treatment planning and implementation	Provides guidance for selecting risk responses
Documentation	Establishes documented information requirements	Supports recording risk assessments and decisions
Monitoring	Requires performance evaluation and continual improvement	Supports ongoing risk monitoring and review
Accountability	Establishes formal roles and responsibilities	Encourages stakeholder involvement in risk management

For example, the institution may identify a risk that the fraud detection system incorrectly flags legitimate transactions.

Using ISO 23894 guidance, the team can assess the potential impact on customers, evaluate the likelihood of incorrect classifications, and determine appropriate safeguards.

These safeguards might include performance testing, human review of certain decisions, monitoring of false-positive rates, and documented escalation procedures.

The institution can manage these activities within its ISO 42001 management system, ensuring that responsibilities, controls, monitoring, and improvement processes remain connected.

This approach helps the organisation avoid treating AI governance and AI risk management as separate activities.

How to implement ISO 23894 and ISO 42001 together

Organisations planning to adopt both standards should begin by establishing clear governance responsibilities and developing a consistent approach to AI risk management.

The following steps provide a practical implementation model. They are not a substitute for the complete requirements and guidance contained in the official standards.

Step 1: Define your AI governance objectives

Start by identifying why your organisation needs a structured AI governance programme.

Objectives may include improving AI risk visibility, supporting regulatory compliance, protecting sensitive information, reducing operational risks, or preparing for ISO 42001 certification.

These objectives should reflect the organisation’s business activities, AI adoption plans, and overall risk management priorities.

Leadership involvement is important because effective AI governance requires coordination across technology, security, compliance, legal, and business functions.

Step 2: Establish an AI management system

Use ISO 42001 to define the scope of your AI management system and establish the necessary governance structure.

This includes developing AI policies, assigning responsibilities, determining relevant organisational requirements, and identifying the resources needed to operate the management system.

Organisations should also define how AI governance will connect with existing information security, enterprise risk management, and compliance activities.

Step 3: Identify and document AI systems

Create an inventory of AI systems used across the organisation.

Include internally developed applications, third-party AI services, generative AI tools, and AI features embedded within existing business software.

For each system, record its purpose, business owner, data sources, provider, operating environment, and relevant dependencies.

This information provides a foundation for conducting risk assessments and determining which systems require additional oversight.

Step 4: Conduct AI risk assessments using ISO 23894 guidance

Apply ISO 23894 guidance to identify and assess risks associated with the AI systems in your inventory.

Consider potential impacts involving cybersecurity, data privacy, accuracy, fairness, transparency, operational performance, and affected stakeholders.

Evaluate identified risks against suitable criteria and determine which risks require treatment.

Risk assessments should be proportionate to the system’s purpose, operating environment, and potential consequences.

Step 5: Implement appropriate risk controls

Once risks have been assessed, determine the controls and treatment measures needed to address them.

These may include access restrictions, data protection measures, model validation, human oversight, vendor assessments, incident response procedures, and performance monitoring.

ISO 42001 provides the management-system structure for planning and controlling relevant activities, while ISO 23894 can inform risk treatment decisions.

Organisations should document control responsibilities and establish processes for evaluating whether the safeguards remain effective.

Step 6: Maintain documentation and evidence

Create consistent records of AI governance activities, risk assessments, treatment decisions, control implementation, approvals, and monitoring results.

Documentation should support internal accountability and provide evidence that the organisation’s processes are operating as intended.

For organisations seeking ISO 42001 certification, maintaining appropriate documented information is particularly important.

Centralising these records can help reduce duplication and make it easier for teams to prepare for internal and external audits.

Step 7: Monitor risks and improve the management system

AI governance and risk management require ongoing attention.

Organisations should review risk assessments when AI systems change, new threats emerge, incidents occur, or business requirements evolve.

They should also evaluate the performance of their AI management system through monitoring, internal audits, management reviews, and corrective actions.

Combining ISO 23894 risk monitoring guidance with ISO 42001 continual improvement requirements helps organisations maintain more consistent oversight.

ISO 23894 vs ISO 42001: Which standard should your organisation choose?

The appropriate choice depends on your organisation’s objectives, existing governance maturity, and need for formal certification.

Choose ISO 23894 when AI risk management is your immediate priority

ISO 23894 may be a suitable starting point if your organisation wants to improve how it identifies, evaluates, and manages AI-related risks.

It can be especially useful when you already have an enterprise risk management programme and want to adapt that programme to address AI-specific risks.

For example, a business introducing a limited number of AI applications may initially focus on strengthening risk assessments, establishing risk ownership, and improving monitoring practices.

Choose ISO 42001 when you need a formal AI management system

ISO 42001 is more appropriate when your organisation needs to establish a structured, organisation-wide approach to AI governance.

It is particularly relevant when leadership wants formal policies, defined responsibilities, documented processes, internal audits, management reviews, and independent certification.

Organisations providing AI products or services to enterprise customers may also consider ISO 42001 when customers require evidence of mature AI governance practices.

Use both standards for a more comprehensive approach

For many organisations, the strongest approach is to use ISO 23894 and ISO 42001 together.

ISO 42001 provides the management-system requirements, while ISO 23894 supports the risk management practices that operate within that system.

This combination can help organisations establish clear governance responsibilities while improving how AI risks are identified, assessed, treated, and monitored.

ISO 23894, ISO 42001, and regulatory compliance

As governments introduce new AI-related laws and regulations, organisations increasingly need to demonstrate how they govern and manage AI systems.

ISO 23894 and ISO 42001 can support these efforts by providing structured approaches to risk management, accountability, documentation, and oversight.

However, neither standard automatically establishes compliance with a specific law.

How the standards relate to the EU AI Act

The EU AI Act establishes legal requirements for certain AI systems and the organisations involved in their development, provision, and use.

Depending on the applicable provisions, obligations may involve risk management, documentation, human oversight, transparency, and other safeguards.

ISO 23894 can help organisations develop structured AI risk assessment practices, while ISO 42001 can support organisational governance and management-system processes.

However, organisations must separately evaluate the AI Act requirements applicable to their roles, systems, and activities.

Certification to ISO 42001 does not automatically demonstrate compliance with the EU AI Act.

Supporting wider governance and compliance programmes

Organisations may also use these standards alongside existing cybersecurity, privacy, and enterprise risk management frameworks.

For example, ISO 27001 supports information security management, while ISO 31000 provides general risk management guidelines.

Using complementary standards can help organisations coordinate their governance activities and reduce duplication between different risk and compliance programmes.

The objective should be to establish a consistent governance structure rather than maintaining separate processes for every framework.

Common challenges when implementing both standards

Although ISO 23894 and ISO 42001 complement each other, organisations may face practical difficulties when implementing them.

Disconnected governance and risk management activities

AI governance policies may be managed by one department, while risk assessments, cybersecurity controls, and compliance records are maintained by others.

This fragmentation makes it difficult to establish a consistent view of AI-related risks and responsibilities.

Organisations should connect these activities through common processes, defined ownership, and coordinated reporting.

Limited visibility into AI applications

Employees may adopt AI tools without formal approval or adequate risk assessment.

This can create gaps in security oversight, data governance, and regulatory compliance.

Maintaining an accurate AI inventory and establishing approval procedures can help organisations identify systems that require additional governance.

Manual risk assessments and evidence collection

Risk and compliance teams may rely on spreadsheets, email, and disconnected documents to manage assessments and supporting evidence.

These approaches can become difficult to maintain as the number of AI systems and regulatory obligations increases.

Standardised workflows and appropriate automation can help improve consistency and reduce administrative work.

Unclear responsibilities for AI risks

AI systems often involve several teams, including IT, cybersecurity, data science, legal, compliance, and business operations.

Without clear responsibilities, risk treatment activities may be delayed and governance decisions may not receive appropriate oversight.

Assigning ownership and establishing escalation procedures can help organisations maintain accountability.

How CyberArrow GRC supports ISO 23894 and ISO 42001 implementation

Implementing AI governance and risk management standards requires organisations to coordinate multiple activities, including risk assessments, policy management, control monitoring, evidence collection, and reporting.

At CyberArrow, we understand that managing these processes through disconnected tools can make governance more complex than necessary.

CyberArrow GRC helps organisations centralise and streamline governance, risk management, and compliance activities through one integrated platform.

Centralised AI risk assessments

Our platform helps organisations conduct structured risk assessments, maintain risk registers, assign ownership, and track remediation activities.

These capabilities can support organisations applying ISO 23894 guidance to identify, evaluate, and manage AI-related risks.

By maintaining risk information centrally, teams can improve consistency and visibility across business functions.

Policy and control management

ISO 42001 requires organisations to establish appropriate governance policies, responsibilities, and operational processes.

CyberArrow GRC helps teams centralise policies, manage controls, assign responsibilities, and maintain records of relevant governance activities.

This supports more consistent oversight and helps reduce the challenges associated with fragmented documentation.

Automated compliance workflows

Our platform helps organisations automate repetitive compliance activities, manage tasks, and coordinate evidence collection.

These capabilities can reduce administrative work and support teams responsible for maintaining documented governance and risk management processes.

Continuous control monitoring

AI systems and their associated risks can change over time.

CyberArrow GRC supports continuous internal control monitoring and compliance tracking, helping organisations maintain visibility into control activities and identify issues requiring attention.

Audit readiness and reporting

Organisations implementing ISO 42001 need reliable records of their management-system activities.

CyberArrow GRC helps centralise evidence, track compliance activities, and provide dashboards and reports that support internal oversight and audit preparation.

While our platform can support the management of relevant governance activities, organisations remain responsible for meeting the applicable requirements of ISO 42001 and determining how ISO 23894 guidance should be applied.

Conclusion: Strengthen AI governance and risk management With CyberArrow GRC

Understanding ISO 23894 vs ISO 42001 is important for organisations seeking to manage artificial intelligence responsibly and establish stronger governance practices.

While ISO 23894 provides guidance for identifying, assessing, treating, and monitoring AI-related risks, ISO 42001 establishes the management-system requirements needed to govern AI activities across an organisation.

Together, these standards help organisations connect AI risk management with policies, responsibilities, operational controls, performance monitoring, and continual improvement.

However, implementing these standards effectively requires more than developing policies and conducting occasional assessments.

Organisations need clear accountability, consistent documentation, structured risk management processes, and ongoing visibility into their controls and compliance activities.

At CyberArrow, we help organisations simplify these challenges through CyberArrow GRC, our integrated governance, risk, and compliance platform.

Our platform helps organisations automate compliance workflows, conduct risk assessments, centralise policies and controls, collect audit evidence, monitor internal controls, and track remediation activities through one centralised system.

By reducing dependence on disconnected spreadsheets and repetitive manual processes, we help GRC teams improve efficiency, maintain accountability, and strengthen audit readiness.

CyberArrow is trusted by the world’s biggest brands across the US, Europe, Africa, Asia and the Middle East. We work to help organisations simplify governance, strengthen risk management, and build more effective compliance programmes.

Whether your organisation is implementing ISO 23894, preparing for ISO 42001 certification, or improving its overall AI governance strategy, CyberArrow GRC can help you manage the supporting risk and compliance activities more efficiently.

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