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Master AI Governance: NIST AI RMF & ISO 42001

Name: Master AI Governance: NIST AI RMF & ISO 42001
Rating: 4.8 (10 reviews)

Implement both frameworks end-to-end — governance, risk, controls, and ISO 42001 certification readiness

Role Play

Created byCyberAI Learning Lab

Last updated 4/2026

English

English [Auto],

What you'll learn

Master the NIST AI RMF's four core functions — GOVERN, MAP, MEASURE, MANAGE — and apply each to real AI risk scenarios
Implement ISO 42001 clause by clause, from context and leadership through audit readiness and certification preparation
Build practical AI governance deliverables: risk registers, AI inventories, lifecycle governance frameworks, and TEVV plans
Integrate NIST AI RMF and ISO 42001 with the EU AI Act, GDPR, ISO 27001, and sector-specific regulations
Design AI governance metrics, dashboards, and reporting structures for boards, executives, and regulators

Course content

16 sections • 60 lectures • 7h 33m total length

Message from the Instrufctor2:21

Introduction1:48
Clarify why AI governance matters amid recent risk shifts, and outline how governance differs from compliance, ethics, and safety, then explore NIST AI RMF and ISO 42001 as implementation-ready options.
The Changing AI Risk Landscape7:20
Explore how AI risk shifted in 2025–2026, see real documented failures, and learn the four risk categories—technical, ethical, operational, legal—while regulatory momentum makes governance non-negotiable.
Defining AI Governance7:47
Define AI governance by distinguishing governance, compliance, ethics, and safety, then implement policy, inventory, risk assessment, and lifecycle oversight using NIST AIRMF and ISO 42001.
Course Overview and Learning Journey6:24
Explore a structured journey through AI governance with NIST AI RMF and ISO 42001, including maturity self-assessment, framework integration, and practical toolkit templates for AIGP and ISO certification prep.

Introduction2:10
Understand NIST AI RMF origins, voluntary stance, relation to cybersecurity, privacy, and NICE frameworks, and the seven trustworthy AI characteristics with framing risk and core.
Background, Development, and Core Premise7:53
Trustworthy AI — The Seven Characteristics8:47
AI RMF Structure and the NIST GenAI Profile6:38
Explore the NIST AI RMF structure, including the four concurrent functions—govern, map, measure, and manage—the generative AI profile, and the practical playbook for managing probabilistic, context-dependent AI risk.

Introduction1:46
GOVERN Overview and Policy Foundation8:39
Accountability, Roles, and Governance Structures8:32
Define AI governance roles, including AI risk owner, AI ethics reviewer, and AI auditor. Build cross-functional boards to oversee AI risk and third-party vendor accountability with meaningful reporting.
Organizational Culture, Teams, and Resources8:41
Design role-specific AI risk literacy training and foster psychological safety to strengthen governance culture. Allocate governance resources with risk-proportionate budgets, incentives, and rigorous third-party vendor due diligence.
AI Risk Management Across the Lifecycle7:01
Explore ai governance lifecycle risk management with stage gates, hand-off protocols, and supply chain risk across data, model, and infrastructure. Learn to draft contractual governance provisions and an implementation plan.
Building the Case for an AI Governance Committee

Introduction1:59
Learn how to perform a map assessment to identify stakeholders, document use cases, define risk context, and classify risks to drive AI governance decisions.
Introduction to MAP and Context Establishment9:00
Scientific Understanding and AI System Classification9:23
Document failure modes, edge cases, and performance boundaries; govern training data provenance, representativeness, and biases; classify risk by consequentiality, reversibility, and human oversight; and maintain a robust ai system inventory.
Risk Identification and Impact Assessment7:44
Challenging a High-Risk AI System Classification
AI System Risk Profile — MAP Function in Practice

Introduction1:49
Learn how to close the gap between risk assessment and action by applying four AI risk response strategies: avoid, mitigate, transfer, or accept, and adapt incident response to AI-specific incidents.
Risk Response Strategies and Planning9:10
Risk Response Implementation and Monitoring10:00
Implement risk-response controls across technical, procedural, and organizational domains in AI governance, addressing bias mitigation, robustness, monitoring with security operations, and audit trails.
AI Incident Response7:43

Introduction2:11
Explore how ISO 42001 provides a certifiable, operational AI governance framework, including the PDCA cycle, clause architecture, and annexes, with integration to other ISO standards.
Background, Purpose, and the PDCA Approach9:40
Learn how ISO 42001 certifies AI governance as a management system, guiding developers, providers, and users through the PDCA cycle, and compare it with NIST AIRMF.
The High-Level Structure and Related Standards10:05

Understanding Context and Interested Parties9:06
Defining AIMS Scope5:32
Define the AIM scope by specifying AI systems, processes, and organizational units, prioritizing high-risk systems and documenting exclusions; communicate and update the scope to meet ISO 42001 and support certification.
Leadership, AI Policy, and Roles7:08
Demonstrate top management commitment under ISO 42001 by drafting a conformant AI policy, assigning governance roles under clause 5.3, and communicating the policy organization-wide, plus clause 4 context analysis.

Introduction2:02
Identify risks and opportunities for AI management system under clause 6.1, and establish governance objectives tied to AI policy, with competence, awareness, and documented information control under clause 7.
Planning: Risks, Opportunities, and Objectives9:05
Support: Resources, Competence, and Awareness7:38
Documented Information9:34
Distinguish documents from records under ISO 42001 clause 7.5, apply versioned governance documents, and enforce access and retention controls for audit-ready evidence.

Requirements

A basic familiarity with risk management, compliance, or organizational governance concepts is helpful but not mandatory
No technical AI or machine learning background is required — this course is designed for governance, risk, and compliance professionals
Learners preparing for the AIGP certification or ISO 42001 implementer roles will find this course directly aligned to those credentials

Description

This course contains the use of artificial intelligence.

AI governance is no longer optional — and frameworks are no longer optional either.

Regulators, customers, boards, and auditors are all asking the same question: can you prove your organization governs AI responsibly? The NIST AI Risk Management Framework and ISO 42001 are the two most widely adopted, implementation-ready answers to that question — and this course teaches you to use both, end to end.

Whether you are building an AI governance program from scratch, preparing for ISO 42001 certification, pursuing the IAPP AIGP credential, or simply trying to understand what these frameworks actually require in practice, this course gives you the depth and the tools to succeed.

What This Course Covers

The NIST AI RMF's four core functions — GOVERN, MAP, MEASURE, and MANAGE — applied through real scenarios and hands-on exercises
ISO 42001 clause by clause — from context and leadership through operation, controls, performance evaluation, and certification readiness
AI inventory and classification systems — how to discover, document, and risk-tier every AI system in your organization
AI lifecycle governance — embedding governance checkpoints from problem framing through decommissioning
Framework integration — connecting NIST AI RMF and ISO 42001 to the EU AI Act, GDPR, ISO 27001, SOC 2, and sector-specific regulations
AI governance metrics, KPI frameworks, and board-level reporting
ISO 42001 certification preparation — gap assessment, documentation, audit readiness, and what auditors actually look for

Who Will Benefit

Risk, compliance, legal, and governance professionals building or overseeing AI governance programs
Technology leaders and AI project managers who need structured governance frameworks to deploy AI responsibly
Professionals pursuing IAPP AIGP certification or ISO 42001 Lead Implementer credentials
Internal auditors and GRC professionals expanding into AI governance
Consultants and advisors who support clients on AI governance and regulatory compliance

Prerequisites

No technical AI or machine learning background is required. A basic familiarity with risk management, compliance frameworks, or organizational governance is helpful. This course is built for governance, risk, and compliance professionals — not for data scientists or AI engineers.

What's Included

Every section of this course includes a chapter quiz to test your understanding before you move forward. The course also includes an initial and a final full-length practice test to benchmark your readiness before attempting the AIGP or ISO 42001 implementer credentials. Three practical assignments — with detailed instructions, sample solutions, and evaluation criteria — are built into the course so you can apply what you learn to real scenarios. Four role play scenarios put you in the room with executives, auditors, product managers, and clinical leaders, practicing the conversations that governance practitioners actually have. And the 15-piece downloadable toolkit — templates, checklists, quick reference guides, and cheat sheets — is yours to use immediately in your organization.

This is not a survey course. It is a complete, implementation-focused program built for professionals who need to do this work, not just know about it.

Who this course is for:

Risk, compliance, legal, and governance professionals tasked with building or overseeing AI governance programs in their organizations
Technology leaders, product owners, and AI project managers who need structured governance knowledge to deploy AI responsibly
Professionals pursuing the IAPP AIGP certification, ISO 42001 Lead Implementer credentials, or a career in AI governance and responsible AI

Master AI Governance: NIST AI RMF & ISO 42001

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 2min

Why AI Governance Matters Now4 lectures • 23min

NIST AI RMF — Architecture & Foundations4 lectures • 25min

NIST AI RMF — GOVERN Function6 lectures • 35min

NIST AI RMF — MAP Function5 lectures • 28min

NIST AI RMF — MEASURE Function4 lectures • 28min

NIST AI RMF — MANAGE Function4 lectures • 29min

ISO 42001 — Overview and Clause Structure3 lectures • 22min

ISO 42001 — Clauses 4 & 5: Context and Leadership3 lectures • 22min

ISO 42001 — Clauses 6 & 7: Planning and Support4 lectures • 28min

Requirements

Description

Who this course is for: