AI Governance Principles | Free Training
September 23, 2025
Understand the core principles that define responsible AI governance and learn how to build systems that are transparent, accountable, and fair.
In this course, we explore the guiding principles of AI governance: accountability, transparency, fairness, and privacy. We also show how each one supports trust, compliance, and ethical decision-making across the AI lifecycle.
You’ll learn how these principles connect to global frameworks such as ISO/IEC 42001, the EU AI Act, and the NIST AI RMF, and how they translate into practical policies, controls, and oversight within your organization.
A few things we cover in this course:
- why governance matters
- the global AI landscape
- the guiding principles of AI governance, both theoretically and in practice
- OECD principles
- the EU AI Act
- ISO/IEC 42001
- NIST AI RMF
Share this article
What is an impact assessment, what does it cover, and how does it help with ISO/IEC 42001? The Safeshield team answers all these questions. Includes downloadable checklist
If you’re looking at professional training in ISO/IEC 42001, Lead Implementer and Lead Auditor are two main options, but how do they compare, and which one is right for you?
If you’re researching AI GRC, ISO/IEC 42001 is one of the standards you’re going to need to understand. For individuals, it’s becoming an important reference point for AI GRC career development. For organisations, it offers a structured way to move from informal AI use or broad responsible AI principles toward a more formal AI management system. ISO/IEC 42001 is an international standard for Artificial Intelligence Management Systems. In simple terms, it gives organisations a framework for managing AI governance, risk, accountability and continual improvement. This guide looks at how an AI Management System works, where ISO/IEC 42001 fits into modern AI governance, and how the right training can prepare professionals to support its implementation or audit.
