Organizations that develop, deploy, or provide AI systems and want a certifiable, auditable framework for AI governance, whether to satisfy customer due diligence, internal risk management, or emerging regulatory expectations like the EU AI Act.
A documented AI management system scope, AI-specific risk assessment and treatment, AI system impact assessments, lifecycle governance covering development through decommissioning, and management review and continual improvement, following the same PDCA structure as ISO 27001.
AI systems introduce risk categories, model behavior, training data provenance, and output reliability, that traditional information security controls don't fully address, requiring governance specific to how AI systems are built, monitored, and retired.
AI system inventory and risk-tier classification, gap assessment against ISO 42001's AIMS requirements, impact assessment process build-out, and readiness review ahead of a formal certification audit.
Inventory AI systems in use or development and assess current governance maturity.
Establish the AIMS documentation, risk assessment, and impact assessment processes.
Support through Stage 1 and Stage 2 certification audits with an accredited body.
AI system inventory, AI-specific risk and impact assessments, AIMS policy documentation, and management review records demonstrating ongoing governance rather than a one-time exercise.
Treating ISO 42001 as a rebrand of existing information security controls instead of building genuinely AI-specific risk and impact assessment processes; scoping the AIMS around only customer-facing AI features while ignoring internal tools with equal or greater risk.
See where your AI systems stand before committing to formal AIMS certification.
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