Definition: AI governance is the set of policies, roles, processes and technical controls an organization uses to make sure its AI systems are lawful, safe, fair, secure and aligned with business goals.
A governance program typically includes an inventory of AI use cases, risk ratings, approval steps before launch, data and privacy rules, model documentation, testing standards, monitoring, incident handling and clear ownership. Public frameworks such as the NIST AI Risk Management Framework and laws such as the EU AI Act shape many programs.
Policies only work if systems produce evidence. Engineers implement access controls, guardrails, evaluation suites, observability traces and human review steps, so risk and compliance teams can see how a system behaves and what changed.
Governance lets an organization move faster with confidence: clear rules mean fewer stalled pilots and fewer surprises after launch, especially in regulated industries.
Ryz AI pod teams build the technical controls governance programs rely on, in your cloud and repositories, working on your team.
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