AI governance is the set of roles, policies, processes, and controls an organization uses to decide how AI is developed and used, and who is accountable when something goes wrong. It connects technical safeguards with organizational decision-making.
This section covers governance fundamentals, AI risk management, established frameworks, regulation, and ethics. Where regulation is discussed, the aim is to explain scope and obligations clearly, not to provide legal advice.
In-depth guides for each topic are in preparation and will be linked here as they are published.
Understand the purpose of AI governance, key responsibilities, and the relationship between technical and organizational controls.
Explore how AI-related risks can be identified, evaluated, documented, and managed.
Learn about established governance frameworks, their scopes, and differences between guidance and requirements.
Understand how relevant AI regulation affects particular systems, organizations, and jurisdictions.
Explore fairness, human rights, accountability, transparency, and other ethical considerations in AI development and use.