ISO 42001 AI Management
Achieve ISO 42001 certification for responsible AI governance
Evidr automates AI risk assessment, lifecycle management, and compliance monitoring. Build trust with customers and regulators through certified responsible AI practices.
Inside the product
ISO 42001 in the console, control by control.

01ISO 42001
The AI lifecycle
The standard follows a system from design to retirement.
- Phase 114
Design & Planning
Define AI system objectives, scope, and requirements. Assess intended use cases and potential impacts.
- Phase 222
Development & Training
Build and train AI models with documented data governance, model selection, and testing protocols.
- Phase 318
Deployment & Operation
Deploy AI systems with monitoring, human oversight, and incident response procedures in place.
- Phase 412
Monitoring & Review
Continuously monitor performance, bias, and compliance. Conduct periodic reviews and updates.
02ISO 42001
Annex A control domains
The domains of Annex A and the controls Evidr maps in each.
- 4Context of the Organization8
- 5Leadership6
- 6Planning12
- 7Support10
- 8Operation16
- 9Performance Evaluation8
- 10Improvement6
- A.2AI Policies4
- A.3Internal Organization5
- A.4Resources for AI Systems6
- A.5Assessing AI System Impacts8
- A.6AI System Lifecycle14
- A.7Data for AI Systems10
- A.8Information for Interested Parties6
- A.9Use of AI Systems7
- A.10Third-party Relationships5
03What Evidr does
Everything ISO 42001 asks for, handled.
- 01
AI Governance Framework
Establish comprehensive AI governance policies, roles, and responsibilities. Define accountability structures for AI system decisions and outcomes.
- 02
AI Risk Assessment
Systematically identify, analyze, and mitigate AI-specific risks including bias, safety, security, and societal impact. Continuous risk monitoring throughout the AI lifecycle.
- 03
AI Lifecycle Management
Manage AI systems from design through deployment and decommissioning. Track model versions, training data, and system changes with full traceability.
- 04
Transparency & Explainability
Document AI system capabilities, limitations, and decision-making processes. Generate explainability reports for stakeholders and regulators.
- 05
Bias Detection & Mitigation
Implement fairness testing across protected attributes. Monitor for bias drift and document mitigation measures with evidence trails.
- 06
Continuous AI Monitoring
Real-time monitoring of AI system performance, accuracy, and drift. Automated alerts for anomalies and compliance deviations.
04The path
ISO 42001 readiness, step by step.
- 01Week 1-3
AI System Inventory
Catalog all AI systems, their purposes, and risk classifications. Map data flows, dependencies, and stakeholders across your AI portfolio.
- 02Week 3-6
Gap Analysis & Risk Assessment
Assess current AI governance against ISO 42001 requirements. Identify gaps in policies, controls, and documentation. Prioritize high-risk AI systems.
- 03Week 6-16
AIMS Implementation
Establish AI Management System policies, procedures, and controls. Implement governance structures, roles, and accountability frameworks.
- 04Week 16-24
Control Implementation
Deploy technical and operational controls for AI risk management, monitoring, transparency, and human oversight. Document evidence of implementation.
- 05Week 24-32
Internal Audit & Certification
Conduct internal audit to validate AIMS effectiveness. Engage accredited certification body for external assessment and certification.
05Questions
ISO 42001, answered.
Related
Often paired with ISO 42001.
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