AI Governance and Risk Management Frameworks – PDF

VIDEO DEMO

BENEFITS OF THIS DOWNLOADABLE PDF DOCUMENT

1. Provides a working command of the NIST AI RMF and ISO/IEC 42001 so auditors can assess AI governance against recognized criteria.
2. Shows how the Three Lines Model applies to AI risk, clarifying assurance roles for the audit function.
3. Includes a NIST AI RMF quick reference, ISO 42001 checklist, and RACI and policy templates ready for immediate use.

ARTIFICIAL INTELLIGENCE PDF DESCRIPTION

AI Governance and Risk Management Frameworks PDF: Learn NIST AI RMF & ISO IEC standards for internal audit. Download expert AI risk and assurance guide now. AI Governance and Risk Management Frameworks is a 45-page PDF document available for immediate download upon purchase.

Effective assurance over AI starts with a clear understanding of how AI should be governed. This is Module 3 of the AI-Powered Internal Audit Professional Series, a 15-module program developed and published by Business Excellence to equip internal audit professionals with practical, standards-aligned AI capability.
This module gives internal auditors a working command of the two most important AI governance and risk frameworks in use today. The NIST AI Risk Management Framework is examined through its four core functions – GOVERN, which establishes the organizational foundation; MAP, which contextualizes AI systems and their risks; MEASURE, which assesses and tracks those risks; and MANAGE, which implements and monitors responses. ISO/IEC 42001, the first certifiable international standard for AI management systems, is examined as a complementary, auditable structure that organizations can be certified against.
Beyond the frameworks themselves, the module shows how established audit and governance concepts apply directly to AI. The Three Lines Model is mapped onto AI risk: the first line owns AI risks within the business, the second line provides specialist oversight and challenge, and the third line – internal audit – delivers independent assurance. The module also addresses what effective AI governance requires in practice: clearly defined accountability from the board through operational levels, and a coherent AI policy suite covering acceptable use, development, vendor management, data, ethics, and incident response.
A central theme is that governance enables innovation rather than constraining it. Evidence indicates that organizations with mature AI governance deploy AI more quickly and more confidently than those without – a message that helps auditors position governance recommendations constructively with management.
The module is aligned with the NIST AI RMF, ISO/IEC 42001, the IIA Global Internal Audit Standards 2024, and the EU AI Act, and reflects current guidance from authoritative bodies including ISACA.
Delivered as a professional PowerPoint presentation with full speaker notes, the module includes a NIST AI RMF quick reference guide, an ISO 42001 implementation checklist, an AI governance RACI template, an AI policy framework template, and a 10-question knowledge assessment quiz – giving audit teams both the understanding and the tools to evaluate AI governance with confidence.

Source: Best Practices in Artificial Intelligence PDF: AI Governance and Risk Management Frameworks PDF (PDF) Document, Amer Morgan