ISO 42001 Certification and Consulting Process

This page covers the ISO 42001 certification process. For ISO 42001 concepts and AI governance, please see the related page.

What Is an ISO 42001 AI Management System?

The ISO/IEC 42001 Artificial Intelligence Management System (AIMS) is an international management system standard for organisations that develop, supply or use AI systems to manage the risks, responsibilities, processes and controls associated with artificial intelligence systematically.

The rapid arrival of AI technologies in corporate business processes has made it important to manage generative AI, large language models (LLMs), machine learning, decision support systems, AI-assisted automation and autonomous systems safely and under control.

ISO/IEC 42001 helps organisations do more than use a single AI technology safely: it helps them establish AI governance across the organisation.

Under its ISO 42001 consulting service, SecureSys analyses an organisation's existing AI usage and supports the establishment of processes such as the AI inventory, AI risk analysis, policies and procedures, the responsibility model, technical and organisational controls, AI impact assessment, supplier controls, internal audit and certification readiness.

The objective is not merely to obtain an ISO 42001 certificate, but to establish a sustainable AI management system in which artificial intelligence is managed in a safe, responsible, transparent, traceable and risk-focused way.

What Is ISO/IEC 42001?

ISO/IEC 42001 provides an Artificial Intelligence Management System – AIMS framework for managing AI systems within an organisation.

The standard addresses areas such as the following through a management system approach:

• AI governance,
• AI policies and procedures,
• AI risk management,
• AI system inventory,
• Roles and responsibilities,
• The lifecycle of AI systems,
• Data management,
• Transparency,
• Human oversight,
• Supplier management,
• Impact assessment,
• Performance monitoring,
• Internal audit,
• Management review,
• Continuous improvement

One of the important characteristics of ISO 42001 is that it does not treat artificial intelligence as a purely technical matter.

AI usage is assessed across the perspectives of:

Technology + People + Process + Data + Risk + Law + Security + Governance

ISO 42001 can therefore be relevant not only to software companies but also to organisations that use AI technologies within their own business processes.

Why Does ISO 42001 Matter?

AI systems can create risks that differ from those of traditional information technology.

The behaviour of a firewall or a database can largely be defined in advance, whereas the outputs of generative AI and machine learning-based systems in particular can vary according to the model used, the training data, the context and the user's input.

This requires organisations to assess new areas of risk.

For example:

• Incorrect AI output
• Hallucination
• Bias and discrimination risks
• Sensitive data being entered into AI systems
• Uncontrolled processing of personal data
• AI models reaching incorrect decisions
• Unauthorised AI usage
• Shadow AI
• Prompt injection attacks
• Model manipulation
• Data poisoning
• Model or data leakage
• Risks arising from third-party AI services
• Intellectual property risks
• Critical decisions being made without human control
• AI output that cannot be explained
• AI service dependencies

can all create new areas of risk for organisations.

The ISO 42001 Artificial Intelligence Management System allows these risks to be identified and controlled under a corporate management model.

What Is an ISO 42001 Certificate?

An ISO 42001 certificate is a management system certificate demonstrating, through an independent certification process, that the organisation has established an Artificial Intelligence Management System meeting the requirements of ISO/IEC 42001.

There is an important distinction to make here:

An ISO 42001 certificate does not guarantee that every AI model the organisation develops or uses is error-free, entirely safe or free of risk.

Certification is aimed rather at showing that the organisation manages its AI-related processes, risks, responsibilities and controls within a systematic management system.

The fundamental approach of ISO 42001 is therefore to answer:

less the question "are we using artificial intelligence?" and more the question "how do we manage artificial intelligence?"

Who Is ISO 42001 Suitable For?

ISO 42001 is not only for technology companies developing AI products.

It can be applied by organisations of different sizes and sectors that develop, supply or use AI systems.

ISO 42001 consulting is worth considering in particular for:

• Companies developing AI software
• Organisations building generative AI solutions
• SaaS companies
• FinTech companies
• Financial institutions
• Banks
• Insurance companies
• Public institutions
• Defence industry organisations
• Healthcare organisations
• Telecommunications companies
• Energy companies
• Manufacturing organisations
• E-commerce companies
• Firms developing human resources technology
• Data analytics companies
• Organisations using contact centre technology
• Companies using AI-based decision support systems
• Organisations integrating large language models into business processes
• Organisations using chatbots or AI agents

What Are the Advantages of an ISO 42001 Certificate?

ISO 42001 work helps organisations manage AI technologies with greater control.

It enables AI risks to be managed

The risks arising from the AI systems the organisation uses or develops are identified and assessed systematically.

It strengthens the AI governance structure

It establishes who takes AI-related decisions, which systems may be used and how responsibilities are distributed.

It brings corporate AI usage under control

It helps manage the shadow AI risks that can arise when employees use uncontrolled AI services.

It supports customer confidence

It allows the organisation to show customers and business partners that it manages its AI usage through defined policies, processes and risk management mechanisms.

It standardises AI risk management

A common risk management methodology is established in place of departments running AI applications independently of one another.

It supports data security

Corporate controls can be established over which data may be entered into AI systems, which information may not be used, and how sensitive data is protected.

It provides an international management framework

It helps organisations operating globally develop their AI governance under a common management system approach.

It delivers continuous improvement

As AI systems and the associated risks change, the management system is reviewed and improved alongside them.

How Does the ISO 42001 Consulting Process Work?

The SecureSys ISO/IEC 42001 consulting service can be tailored to the organisation's existing AI usage, organisational structure and objectives.

The general working model consists of the following stages.

1. Defining the ISO 42001 Scope

The scope of the Artificial Intelligence Management System is defined first.

Which company, department, location, process, AI system or service will be included is assessed.

When scope is set, the organisation's:

• AI use areas
• AI products
• AI services
• AI integrations
• Data sources
• Critical business processes
• Customer requirements
• Suppliers
• Legal and contractual obligations

are all taken into account.

ISO 42001 Gap Analysis

An ISO 42001 gap analysis is carried out to establish the extent to which the organisation's existing AI governance and AI risk management structure meets the requirements of ISO/IEC 42001.

Existing policies, processes, technologies, AI use areas, responsibilities and technical controls are assessed.

Each finding can be reported using the approach:

ISO 42001 Requirement → Current State → Gap → Risk → Recommended Action → Owner → Priority → Target Date

This exercise allows the organisation to see its current maturity level before starting the ISO 42001 certification process.

Building the AI Inventory

One of the most important steps in ISO 42001 work is identifying the AI systems in use across the organisation.

Organisations often have AI tools in use without the knowledge of the central IT function.

Employees may, for example, use generative AI platforms such as ChatGPT, coding assistants, AI-assisted design tools, translation systems, meeting assistants or various SaaS AI services.

An AI inventory is therefore built.

The inventory can track information such as:

• The name of the AI system
• Its purpose
• The system owner
• User groups
• The model used
• Data sources
• Types of data processed
• Whether personal data is involved
• Use of critical data
• Supplier information
• Integrations
• Risk level
• Human oversight
• The intended use of the output

What Is Shadow AI and How Is It Managed?

Shadow AI is the use of AI tools without the knowledge and approval of the organisation's IT, information security or governance teams.

Employees uploading customer information, source code, contracts, financial data, personal data or corporate documents to free or personal AI services can create serious data security and privacy risks.

To manage shadow AI risks under ISO 42001:

• Approved AI tools can be defined.
• Prohibited use cases can be specified.
• Usage rules can be established according to data classification.
• An AI acceptable use policy can be prepared.
• AI awareness training can be delivered to employees.
• Technical security controls can be applied.
• AI usage processes can be monitored.

The aim is controlled and secure AI usage rather than banning artificial intelligence outright.

ISO 42001 AI Risk Analysis

AI risk assessment is one of the core components of an ISO 42001 management system.

The potential effects of the AI systems used or developed on the organisation, its employees, its customers and other interested parties are assessed.

The risk analysis can establish the relationship:

AI System → Use Case → Threat/Risk → Impact → Likelihood → Existing Controls → Risk Level → Action

AI risks have to be assessed more broadly than classic cyber security risks.

What Are the Risks of Artificial Intelligence?

Different risk categories can be assessed in ISO 42001 consulting work according to the organisation's use cases.

Data privacy risk

Transferring personal, confidential or sensitive information to AI systems can create data security risk.

Incorrect output risk

AI systems can produce results that appear correct but are contrary to fact.

This can have significant consequences particularly in financial, legal, healthcare or other critical decision processes.

Bias risk

Imbalances in the training data of AI models can lead to unintended outcomes for particular individuals or groups.

Explainability risk

In some AI systems it can be difficult to explain why a particular result was produced.

Model security

The manipulation, misuse or unauthorised access of AI models has to be assessed.

Prompt injection

In LLM-based applications, inputs crafted by an attacker can cause the model to behave unexpectedly or security controls to be bypassed.

Data poisoning

Manipulating the data used in model training or learning processes can affect model behaviour.

Model and data leakage

The risk of sensitive information being exposed through model outputs or AI integrations has to be assessed.

Third-party AI risk

The security, data processing, continuity and contractual terms of external AI providers can affect the organisation.

Lack of human oversight

Leaving critical decisions entirely to automated AI systems can create operational and governance risk.

AI Impact Assessment

An AI impact assessment aims to evaluate systematically the effects an AI system may have on individuals, the organisation, customers and other interested parties.

Impact assessment is important in particular for AI systems that:

• Make decisions about people,
• Build profiles,
• Evaluate employees,
• Produce credit or risk scores,
• Influence critical decisions,
• Process personal data,
• Use automated decision mechanisms

The assessment can address not only technical performance but also:

fair use, transparency, human oversight, data privacy, security and potential adverse effects

AI Governance

AI governance is the establishment of the organisation's decision, responsibility and control mechanisms over its AI systems.

In a good AI governance model, the answers to questions such as the following are clearly defined:

Who may use an AI system?

Which AI tools may be used?

Which data may be transferred to AI systems?

Who approves a new AI project?

Who assesses AI risks?

Who is responsible for model outputs?

Is human approval required for critical decisions?

Who evaluates the AI supplier?

A structure such as an AI committee / AI governance committee can be established within the organisation for this purpose.

ISO 42001 Policies and Procedures

For an ISO 42001 management system to be sustainable, policies and procedures appropriate to the organisation's structure have to be established.

Depending on scope, documents such as the following can be prepared:

• Artificial Intelligence Management Policy
• AI Governance Policy
• AI Acceptable Use Policy
• AI Risk Management Procedure
• AI Inventory Management Procedure
• AI System Approval Process
• AI Impact Assessment Procedure
• AI Supplier Assessment Procedure
• Data Management Policy
• AI Security Policy
• Human Oversight Procedure
• AI Incident Management Procedure
• AI Change Management
• AI Performance Monitoring Process
• Generative AI Usage Rules
• AI Lifecycle Management

The purpose of the documents is not merely to create records for an ISO 42001 audit, but to manage the organisation's real AI usage.

ISO 42001 Technical Work

In the SecureSys ISO 42001 consulting service, the work is not limited to documentation and establishing a management system.

In line with the scope and the technology in use, the technical security architecture of the AI systems can also be assessed.

The technical work can include:

• Review of the AI system architecture
• Assessment of LLM integrations
• Review of AI API security
• Authentication and authorisation controls
• Assessment of access permissions to AI systems
• Analysis of data flows
• Review of sensitive data usage
• Assessment of prompt and output security
• Review of prompt injection risks
• Assessment of sensitive information disclosure risks
• Review of model access controls
• Assessment of AI system logs
• Verification of the traceability of AI activity
• Review of API key and secret management
• Assessment of AI service provider security controls
• Review of model and data integrity controls
• Assessment of rate limiting and abuse prevention mechanisms
• Review of secure development controls in AI applications
• Assessment of AI agent permissions and access
• Security review of the RAG architecture
• Assessment of vector database access
• Assessment of the SIEM/SOC integrations of AI systems
• Review of DLP and data classification controls
• Assessment of the security configuration of cloud AI services
• Identification of shadow AI usage risks

This approach allows the ISO 42001 requirements to be assessed not only on paper but against the organisation's real AI technologies and AI use cases.

Generative AI Security

The spread of generative AI services such as ChatGPT has created a new security area for organisations.

Generative AI security covers what information users may share with AI systems, how AI outputs are used, and how integrations are protected.

An employee uploading the following to a generative AI system, for example, has to be assessed from a data security perspective:

• Source code
• Customer data
• Trade secrets
• Personal data
• Financial data
• Contracts
• Security configuration

Establishing generative AI usage policies is therefore an important control area under ISO 42001.

LLM Security and ISO 42001

In applications using a large language model – LLM, security risks specific to AI systems have to be assessed alongside classic web application security.

Risks such as prompt injection, sensitive information disclosure, insecure output handling, over-privileged AI agent structures and third-party model dependencies in particular can be brought into the assessment.

An ISO 42001 management system supports the inclusion of these technical risks in the organisation's overall AI risk management process.

AI Agent Security

Unlike classic chatbots, AI agent systems can communicate with other applications, call tools and carry out certain operations automatically.

This makes AI agent security critical.

For an AI agent, the following have to be established:

which systems it can access, which operations it can perform, on whose behalf it acts, and in which situations it requires human approval

A human-in-the-loop approach should be considered for critical operations in particular.

AI Data Management

The success of AI systems depends largely on the data they use.

Data management is therefore an important area of work under ISO 42001.

The following can be assessed for the data:

• Its source
• Its quality
• Its accuracy
• How current it is
• Its classification
• Its retention period
• Access permissions
• Whether it contains personal data
• The purpose for which it is used in the AI system

Knowing the source of, and the right to use, the data used in model training, fine-tuning or a RAG architecture is particularly important.

What Is the Difference Between ISO 42001 and ISO 27001?

The two standards can complement one another, but they do not share the same purpose.

ISO/IEC 27001 focuses on the information security management system.

ISO/IEC 42001 focuses on the artificial intelligence management system.

Holding an ISO 27001 certificate does not automatically mean ISO 42001 compliance.

In organisations with an ISO 27001 management system, however, existing processes such as policy management, risk management, internal audit, management review and continuous improvement can offer a significant advantage in ISO 42001 work.

Topic	ISO 27001	ISO 42001
Main area	Information security	AI management
Management system	ISMS	AIMS
Core focus	Protecting information	Responsible management of AI
Risk	Information security risks	AI-driven risks and impacts
Data	Information assets	Data used by and given to AI
Governance	Information security	AI governance
Technical security	Broad in scope	Controls specific to AI systems

ISO 42001 and the NIST AI Risk Management Framework

The NIST AI Risk Management Framework (AI RMF) is one of the important international frameworks for managing AI risk.

ISO 42001 focuses on establishing a corporate structure from a management system perspective.

Depending on the organisation's needs, ISO 42001 and the NIST AI RMF can be assessed together.

This approach allows the structure of:

AI governance + AI risk management + technical controls + continuous improvement

to be addressed more comprehensively.

ISO 42001 and the EU AI Act

The European Union's artificial intelligence regulation has created an important area of compliance, particularly for organisations operating in the European market or supplying AI systems to it.

The EU AI Act and ISO 42001 are not the same thing.

The EU AI Act is a legal regulation, whereas ISO/IEC 42001 is an international management system standard that can be adopted voluntarily.

The mechanisms established under ISO 42001, however, can create a strong governance foundation that supports organisations' AI compliance work:

• AI governance
• AI risk management
• AI inventory
• Roles and responsibilities
• Data governance
• Transparency processes
• Human oversight
• Record-keeping and traceability
• Supplier management
• Continuous monitoring

It should not be forgotten that an ISO 42001 certificate on its own does not mean EU AI Act compliance.

ISO 42001 and KVKK

Where AI systems process personal data, KVKK obligations have to be assessed separately.

Transferring customer data to AI systems, analysing employee information with AI, building profiles from personal data or sending personal data to third-party AI services, for example, can all require assessment from a personal data protection perspective.

The data governance and AI risk management processes established under ISO 42001 can support KVKK compliance work, but an ISO 42001 certificate on its own does not mean KVKK compliance.

ISO 42001 and GDPR

In AI systems processing personal data under GDPR, matters such as data minimisation, purpose limitation, transparency and data subject rights are important.

AI use cases involving automated decision-making and profiling in particular have to be assessed separately.

The AI governance model developed under ISO 42001 can help the organisation track the personal data risks in its AI systems systematically.

AI Supplier Risk Management

Organisations may not develop all of their AI technology in-house.

Many organisations use third-party:

• LLM providers
• SaaS AI platforms
• Cloud AI services
• AI API services
• Data providers
• Model providers

AI third-party risk management is therefore one of the important areas of ISO 42001 work.

When suppliers are assessed, the following can be examined:

where the data is processed, whether the data is used in model training, retention policies, security certifications, sub-processors, data breach processes, service continuity and contractual terms

Human Oversight

Human oversight becomes important where AI systems are used in critical decision processes.

Depending on the organisation's use case, AI output may need to be checked by an authorised person rather than applied directly.

This approach is described as human-in-the-loop.

Under ISO 42001, it can be defined which processes require human oversight and under what conditions AI output may be rejected or amended.

AI Transparency and Explainability

Making it possible to understand how AI systems are used and which decisions they influence is one of the important components of a trustworthy AI approach.

AI transparency and AI explainability work can assess:

the purpose of AI use, data sources, system boundaries, known limitations, human oversight and decision mechanisms

Explainability can become more critical in processes where AI output has a significant effect on people.

AI Incident Management

Security or operational incidents can also occur in AI systems.

The following, for example, can be treated as AI incidents:

• Sensitive data leakage
• Incorrect model output
• Model manipulation
• Prompt injection
• Unauthorised AI usage
• AI service outage
• Data integrity problems
• A critical incorrect decision

Processes can be established under ISO 42001 for these events to be detected, recorded, analysed, escalated and prevented from recurring.

AI System Lifecycle Management

AI systems should not be assessed only at the moment they go live.

With an AI lifecycle management approach, all of the following stages can be kept under control:

Idea → Design → Development → Test → Approval → Go-Live → Monitoring → Change → Retirement

Different risk and control requirements can be applied at each stage.

ISO 42001 Internal Audit

An ISO 42001 internal audit assesses whether the Artificial Intelligence Management System operates in line with the requirements of the standard and with the organisation's own policies and procedures.

The internal audit can assess:

• AI governance
• AI risk management
• The AI inventory
• AI impact assessment
• Policies and procedures
• Roles and responsibilities
• Technical controls
• Supplier management
• Records
• Performance indicators
• Corrective actions

An internal audit carried out before the certification audit allows gaps to be identified at an early stage.

ISO 42001 Management Review

Managing an ISO 42001 system through technical teams alone is not sufficient.

Senior management has to assess the system's performance and the AI risks regularly.

The management review can address:

AI risks, significant incidents, performance indicators, internal audit results, corrective actions, new AI projects, resource requirements and improvement opportunities

This approach ensures that AI governance is owned at senior management level.

How Is an ISO 42001 Certificate Obtained?

An organisation wishing to obtain an ISO 42001 certificate first has to establish an Artificial Intelligence Management System that meets the standard.

The general process can proceed as:

Scope Definition → Gap Analysis → AI Inventory → AI Risk Analysis → Impact Assessment → Policies and Procedures → Controls → Training → Internal Audit → Management Review → Corrective Actions → Certification Audit

The certification audit is carried out by an independent certification body with the appropriate competence.

SecureSys provides consulting and compliance support to prepare the organisation for the ISO 42001 requirements during this process.

Is an ISO 42001 Certificate Mandatory?

ISO/IEC 42001 is generally a management system standard that organisations may adopt, and on its own it does not constitute a legal obligation for every company.

ISO 42001 can nonetheless become an important requirement because of:

customer demands, supplier security assessments, contractual requirements, international projects or the organisation's own AI governance objectives

The standard offers an important governance framework particularly for organisations that develop AI technology or use artificial intelligence heavily in critical processes.

How Long Does It Take to Obtain an ISO 42001 Certificate?

The ISO 42001 certification timeline varies according to the organisation's size and the complexity of its AI usage.

The duration can be affected by:

• The number of AI systems
• Use cases
• The number of locations
• Existing management systems
• The complexity of the AI risks
• The current state of policies and procedures
• The number of AI suppliers
• Technical security gaps
• Existing management system certifications such as ISO 27001
• The time needed to complete corrective actions

Carrying out an ISO 42001 gap analysis first is therefore the sounder way to produce a realistic estimate.

How Are ISO 42001 Consulting Fees Determined?

ISO 42001 consulting fees vary according to the organisation's scope and the size of its AI ecosystem.

Pricing can take into account factors such as:

the number of employees, the number of AI systems, the AI products developed, the third-party models in use, locations, existing documentation, the scope of the risk analysis, the need for technical assessment, training, internal audit and certification readiness

Scoping ISO 42001 consulting to the organisation's real AI usage is therefore more appropriate than offering a fixed package.

ISO 42001 Training

SecureSys can deliver awareness and implementation training under ISO 42001 according to the organisation's needs.

The training can cover topics such as:

• The core requirements of ISO/IEC 42001
• AI management systems
• AI governance
• AI risk management
• AI impact assessment
• Generative AI risks
• Shadow AI
• Data security
• AI supplier risks
• Human oversight
• AI security
• Internal audit and the certification process

Different training content can be produced for technical teams, managers and end users.

ISO 42001 Consulting Deliverables

Depending on the scope of the SecureSys ISO 42001 consulting project, the following can be produced:

• ISO 42001 Gap Analysis Report
• AI Inventory
• AI Risk Register
• AI Risk Assessment Methodology
• AI Impact Assessment
• AI Governance Model
• AI Roles and Responsibilities Matrix
• AI Management Policy
• Generative AI Usage Policy
• AI Acceptable Use Policy
• AI Risk Management Procedure
• AI Supplier Assessment Process
• Data Management Controls
• Technical Security Assessment
• AI Incident Management Process
• AI KPI/KRI Set
• Corrective Action Plan
• Internal Audit Report
• Management Review Preparation
• Certification Readiness Report
• ISO 42001 Roadmap

Why SecureSys for ISO 42001 Consulting?

In ISO 42001 work, interpreting the clauses of the standard and preparing documentation is not sufficient on its own.

The real technical risks of AI systems also have to be understood.

SecureSys approaches ISO 42001 work by bringing together the perspectives of:

GRC + cyber security + AI governance + AI risk management + data security + technical security

This approach also assesses how the controls defined in policy will be applied in AI applications, LLM integrations, APIs, data flows, cloud services and user processes.

The objective is not merely to pass the ISO 42001 audit, but to establish a secure and sustainable Artificial Intelligence Management System within the organisation.

ISO 42001 Consulting Proposal

If your organisation uses ChatGPT, Microsoft Copilot, generative AI, LLMs, AI agents, machine learning or other artificial intelligence technologies, or offers AI-based products to your customers, establishing AI governance processes systematically is becoming steadily more important.

Under its ISO/IEC 42001 Artificial Intelligence Management System consulting, SecureSys can support your organisation across current-state and gap analysis, the AI inventory, AI risk analysis, AI impact assessment, the development of policies and procedures, technical security assessments, training, internal audit, management review and certification readiness.

Request a proposal for ISO 42001 certification, ISO 42001 consulting, AI governance, AI risk management and ISO 42001 certification readiness.

Frequently Asked Questions About ISO 42001

What does ISO 42001 stand for?

ISO/IEC 42001 is the international standard for artificial intelligence management systems. It helps organisations manage their AI usage systematically from a governance, risk, process and control perspective.

What is AIMS?

AIMS – Artificial Intelligence Management System is the management system structure ISO 42001 aims to establish.

Who can obtain ISO 42001?

Organisations that develop, supply or use AI can establish an ISO 42001 management system within their own scope and activities and apply for the appropriate certification process.

Is ISO 42001 only for software companies?

No. Organisations using artificial intelligence in finance, the public sector, defence, healthcare, manufacturing, energy, retail and other sectors can also consider ISO 42001.

Do companies using ChatGPT need ISO 42001?

An organisation using ChatGPT or another generative AI service does not automatically become obliged to obtain an ISO 42001 certificate. Using these tools with corporate data can, however, increase the need for AI governance and risk management.

If we have ISO 27001, do we need ISO 42001?

The two standards focus on different areas. ISO 27001 addresses information security, ISO 42001 addresses artificial intelligence management. An existing ISO 27001 management system can make ISO 42001 work easier but does not deliver ISO 42001 compliance directly.

Are ISO 42001 and the EU AI Act the same?

No. ISO 42001 is a management system standard; the EU AI Act is the European Union's legal regulation on artificial intelligence. Although there are areas in which they support one another, neither replaces the other.

What is an ISO 42001 risk analysis?

It is the systematic assessment of the security, data, operational, human, governance and other effects that the AI systems an organisation develops or uses may create.

What is an ISO 42001 gap analysis?

It is the identification of the differences between the organisation's existing AI management structure and the requirements of ISO/IEC 42001. It is one of the important pieces of work to carry out at the start of a certification project.

What does ISO 42001 consulting cover?

Scope definition, gap analysis, AI inventory, AI risk analysis, impact assessment, policies and procedures, technical controls, training, internal audit, management review and certification readiness can all be included.

Bring Your Artificial Intelligence Under Control and Prepare for What Comes Next

As AI technologies develop rapidly, what matters is not only that organisations use AI but that they manage these technologies in a safe, controlled, traceable and sustainable way.

With SecureSys ISO/IEC 42001 Artificial Intelligence Management System consulting you can establish your AI governance structure, analyse your AI risks, put your policies and controls into practice, and prepare for the certification process systematically.

Don't just use artificial intelligence — manage it properly.

Request a proposal for your ISO 42001 compliance and certification process.