Govern AI responsibly with a certified AIMS framework.
CalVant helps you implement ISO 42001 — the world's first international standard for AI management — with mapped controls, risk-based governance, and clear accountability across your AI lifecycle.
AI systems monitored · 38 controls active
What is ISO 42001?
ISO/IEC 42001:2023 is the world's first international standard for establishing, implementing, maintaining and continually improving an Artificial Intelligence Management System (AIMS).
AI-specific governance
Define scope, context, and objectives for AI systems. Establish policies and controls proportionate to the risks AI introduces to your organization and society.
Risk-based AI decision-making
Identify AI-specific threats such as bias, opacity, and misuse. Evaluate risks across the AI lifecycle and select proportionate treatment options.
Continuous improvement loop
Use audits, monitoring, incidents and metrics to drive corrective actions and keep AI controls effective as models and environments evolve.
Core ISO 42001 clauses
Clauses 4–10 mirror the High Level Structure (HLS) approach used by ISO 27001, making integration straightforward for organizations already certified or working toward ISO 27001.
Context of the organization
Understand internal and external issues, interested parties, and the scope of your AIMS.
- Define which AI systems fall within scope.
- Understand AI-related legal and societal expectations.
- Align AI objectives with organizational strategy.
Leadership and commitment
Ensure top management is visibly accountable for responsible AI use.
- Assign AI governance roles and authorities.
- Establish an AI policy aligned with values.
- Integrate AI governance into organizational processes.
Planning and risk management
Address AI-specific risks and define measurable AI governance objectives.
- Conduct AI impact assessments.
- Develop risk treatment plans for AI systems.
- Plan how objectives will be achieved and measured.
Support
Provide resources, competence, awareness and documented information for AI governance.
- Build AI literacy across the organization.
- Maintain documentation of AI system design decisions.
- Communicate AI policies to relevant stakeholders.
Operational planning and control
Plan, implement and control processes needed to meet AI governance requirements.
- Manage AI system development and deployment.
- Control third-party AI providers and data processors.
- Maintain records of AI decisions and their rationale.
Performance evaluation & improvement
Measure AIMS performance, run internal audits, and drive continual improvement.
- Monitor AI system KPIs and fairness metrics.
- Conduct regular management reviews of AI governance.
- Implement corrective actions for AI incidents.
Annex A & B controls
ISO 42001 provides two annexes of controls: Annex A for organizations developing or using AI, and Annex B for organizations providing data or other resources for AI systems.
Purpose-built AI controls
Unlike general IT security frameworks, ISO 42001 controls address the unique challenges of AI: bias, explainability, data provenance, and model drift — making it the definitive standard for trustworthy AI.
AI policy & governance
Organizational policies and governance structures for responsible AI development and deployment.
- AI use policy and acceptable use guidelines
- Roles, responsibilities and accountability
- AI procurement and vendor governance
- Stakeholder engagement and communication
AI risk & impact assessment
Systematic evaluation of risks introduced by AI systems across their lifecycle.
- AI risk assessment methodology
- AI impact assessment for high-risk systems
- Bias and fairness evaluation
- Societal and ethical risk considerations
AI system lifecycle
Controls that govern how AI systems are designed, trained, tested, deployed and retired.
- Data quality and data governance
- Model development and validation practices
- Testing, evaluation and performance monitoring
- Decommissioning and model retirement
Transparency & explainability
Measures that ensure AI decisions can be understood, explained and challenged by affected parties.
- Explainability requirements by risk level
- Documentation of model decision logic
- User and subject information rights
- Human oversight and intervention mechanisms
Security & robustness
Controls ensuring AI systems are secure against adversarial attacks and operate reliably.
- Adversarial attack detection and prevention
- Model robustness testing
- Data poisoning and integrity controls
- Incident response for AI failures
Business impact of ISO 42001
Beyond certification, a well-run AIMS helps you deploy AI confidently, build stakeholder trust and meet emerging AI regulations.
Meet AI regulation requirements
ISO 42001 aligns with the EU AI Act, NIST AI RMF, and emerging national AI governance frameworks — simplifying multi-jurisdictional compliance.
Demonstrate trustworthy AI
Certification proves your AI systems are governed systematically — not just promised. Build confidence with customers, regulators and partners.
Manage AI-specific risks
Address bias, opacity, hallucination and misuse through structured risk assessment and treatment — before they cause harm or reputational damage.
Improve AI transparency
Explainability and human oversight controls ensure affected individuals and stakeholders can understand and challenge AI-driven decisions.
Integrate with existing ISMS
ISO 42001 shares the High Level Structure with ISO 27001, allowing you to integrate both management systems efficiently with minimal duplication.
Align AI stakeholders
A documented AIMS clarifies responsibilities for data scientists, developers, legal, and executives — reducing AI governance gaps and overlaps.
Ready to make ISO 42001 your AI governance advantage?
See how CalVant helps you build a modern AIMS, govern AI systems responsibly and stay ahead of emerging regulations.