AI Governance & ISO/IEC 42001
Learn how to build and operate an AI Management System (AIMS) using international best practices — AI risk management, impact assessments, and the ISO/IEC 42001 framework.
Coming SoonBuild your enterprise AI Governance program in 2.5 weeks. Thirteen to fifteen instructor-led sessions produce a complete governance toolkit — charter, playbook, policies, risk framework, vendor process, incident response, and executive dashboard — that you take back to your organization.
View the intensive →What you'll learn
The path is grounded in the ISO/IEC 42001 clauses and Annex A controls that a real audit will look for — not theory disconnected from operating reality.
Governance structures, accountability, executive reporting, and how AI oversight sits inside an existing ISO 27001-based management system.
The full clause-by-clause structure — Context, Leadership, Planning, Support, Operation, Performance Evaluation, Improvement — plus Annex A controls.
How to identify AI-specific risks, run AI Impact Assessments, and integrate the outputs into your enterprise risk register.
Vendor questionnaires, contractual controls, and monitoring for AI suppliers and integrated AI services.
Human oversight, transparency, explainability, and bias detection — the ethical controls that ISO/IEC 42001 makes auditable.
AI-specific incident scenarios: model drift, prompt injection, hallucination-driven decisions, data leakage through AI outputs.
How ISO/IEC 42001 aligns with the NIST AI Risk Management Framework, the EU AI Act, ISO/IEC 27001, and ISO/IEC 27701.
Building the AI Policy, AI Inventory, Risk Register, and Statement of Applicability that a certification audit needs to see.
Internal audit, management review, and how to keep an AIMS operating between certification cycles.
Who it's for
CISOs, DPOs, and privacy officers adding AI to their governance scope. Practical guidance on integrating an AIMS with an existing 27001 / 27701 system rather than building a parallel program.
Risk, compliance, and governance managers expanding into AI oversight. Focus on evidence, controls mapping, and audit readiness — not high-level ethics theory.
Internal auditors and external assessors preparing to audit AI systems. Clause-by-clause interpretation and the evidence that satisfies each control.
Engineers, product managers, and program leads responsible for standing up the AI Management System their organization has committed to.
Expected launch timeline
We build slowly and honestly. Question banks are practitioner-written, not scraped. Here's the plan.
Email admin@techgics.com and we'll notify you when the first module goes live. We reply within 1–2 business days.