AI Governance & Risk
Trending now. Practical guidance on governing AI systems, managing AI risk and preparing for emerging AI regulation and assurance expectations.
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Core topics
ISO/IEC 42001 — AI Management System
AIMS scope, AI policy, risk assessment and how ISO/IEC 42001 maps to existing management systems.
AI risk management
Identifying AI-specific risks, impact assessment, model lifecycle controls and risk treatment in practice.
EU AI Act readiness
Risk classification, prohibited practices, high-risk system obligations, conformity and record-keeping.
Responsible AI governance
Accountability, transparency, human oversight, bias handling and board-level AI governance.
Algorithmic assurance
Auditing AI systems, internal validation, third-party assurance and evidence buyers expect.
AI + Information Security
How AI tools interact with ISO/IEC 27001, data protection, supplier security and access controls.
Questions and resources in AI Governance & Risk
AI governance discussion — open community threads
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Frequently asked
Do I need ISO/IEC 42001 to use AI responsibly?
No — but it provides a structured management system. Many organisations adopt its principles before formal certification.
Does the EU AI Act apply to UK organisations?
It applies if you place AI systems on the EU market or use them in the EU. The Act is shaping global expectations.
Can we integrate AI governance into an existing ISO/IEC 27001 or 9001 system?
Yes. Integration is practical and recommended rather than running a separate AI-only system.
What evidence do auditors and buyers want?
Risk registers, impact assessments, policy documents, test records, oversight logs and supplier due diligence.
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