Foundational educational content
Clear, executive-grade explanations of the core concepts that underpin every AI governance program: governance, trust, and responsibility.
What Is AI Governance?
AI governance is the operating system organizations use to direct, oversee, and account for the AI they deploy. It is a discipline, not a document.
What Is AI Trust?
AI trust is the demonstrable confidence that stakeholders — customers, regulators, employees, and boards — place in an organization's use of AI. It is the outcome that governance is meant to produce.
What Is Responsible AI?
Responsible AI is the set of principles, design practices, and controls organizations use to ensure AI is fair, transparent, accountable, safe, and respectful of human oversight. It is operational, not aspirational.
The EU AI Act is the world's first comprehensive horizontal AI regulation. It categorizes AI systems by risk (prohibited, high-risk, limited-risk, minimal-risk) and imposes obligations on providers, deployers, importers, and distributors operating in or selling into the EU.
ISO/IEC 42001 is the first international management-system standard for artificial intelligence. It defines requirements for establishing, implementing, maintaining, and continually improving an AI management system (AIMS), with certifiable controls across governance, risk, lifecycle, and operations.
The NIST AI Risk Management Framework is a voluntary, widely adopted framework for managing risks across the AI lifecycle. It is organized around four functions — Govern, Map, Measure, Manage — and is paired with the Generative AI Profile for foundation-model risks.