ISO/IEC 42001 — AI Management System
Demonstrate responsible AI to customers, regulators and boards.
ISO/IEC 42001 (2023) is the first international standard for AI Management Systems — covering governance, risk, lifecycle, transparency and stakeholder impact. Macksofy implements 42001 alongside the EU AI Act / DPDP / sectoral guidance for organisations shipping AI to enterprise.
- ISO/IEC 42001:2023
- EU AI Act (risk-tier mapping)
- NIST AI Risk Management Framework
- Macksofy AI Risk Taxonomy
- DPDP / GDPR — automated decision-making provisions
Compliance is leverage, not paperwork.
Boards, customers and regulators are asking 'how do you govern your AI?' Answers like 'we have an internal policy' no longer cut it. ISO 42001 audited certification — alongside DPDP / EU AI Act readiness — is fast becoming a procurement-stage requirement, especially for AI sold into BFSI, healthcare and government.
- AI / ML product companies + LLM application builders
- Banks + insurers using AI for underwriting / claims
- Healthtech using AI for diagnostics / triage
- Edtech / hiring-tech using AI for evaluation
- Cloud + SaaS embedding generative AI features
Aligned to the regulations that matter.
How we run a ISO 42001 engagement.
Interactive walkthrough — every phase clickable, every activity documented, every artefact regulator-ready.
1 · AI inventory + risk tiering
- Inventory of AI systems + use cases
- Risk tiering (EU AI Act categories)
- Stakeholder impact assessment
Everything you need to satisfy auditors.
- AI inventory + risk-tier register
- AI policy + 7+ procedures
- Bias / fairness / explainability evidence pack
- Incident playbook + audit log spec
- Stage 1 / 2 audit support
- EU AI Act gap mapping
First ISO 42001 + EU AI Act readiness
Outcome: Cleared diligence at two strategic investors and one EU enterprise deal on the strength of certified AI governance
The shape of a ISO 42001 engagement.
Every number below is grounded in how Macksofy actually runs the engagement — not aspirational marketing copy.
What we actually examine.
Each pillar is a distinct workstream inside the engagement — scoped, evidenced, and signed off independently before the audit pack is assembled.
- AI policy & governance3 pts
- AI risk assessment & impact3 pts
- Data & model lifecycle3 pts
- Bias, fairness, transparency3 pts
- AI incident handling3 pts
- AI compliance & assurance3 pts
The first thing 42001 auditors ask: who owns AI risk at your organisation?
- AI policy + ethics charter
- AI governance board + RACI
- AI use-case inventory
AI system risk is not classical InfoSec risk. We assess it as a distinct domain.
- AIIA — AI Impact Assessment
- Model risk tiering (low / med / high)
- Stakeholder-impact analysis
From dataset to deployment to decommissioning.
- Training-data lineage + consent
- Model versioning + reproducibility
- Decommissioning & retention policy
The differentiator from any prior ISO standard.
- Bias-testing methodology + thresholds
- Explainability artefacts per model
- Human-in-the-loop checkpoints
What happens when the model goes wrong in production.
- AI-incident detection + escalation
- Model rollback / kill-switch evidence
- Affected-party notification playbook
Internal audit + third-party assurance specific to AI systems.
- AI internal-audit programme
- Vendor-AI due diligence
- Annual AI-system attestation
From kick-off to regulator-ready report.
The horizontal flow below shows the typical week-by-week shape of a ISO 42001 engagement. Click any station for detail in the methodology section above.
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