AI governance

AI governance

AI

AI governance is the policies, controls and records a business uses to decide how AI is used, what it may do and who is accountable for its work.

What is AI governance?

AI governance answers practical questions: which AI tools are approved, what data they may see, which actions need a person's sign-off, how work is recorded and who reviews it. For agents that act, governance moves from documents into product settings. The building blocks are access per agent (least privilege), approvals for consequential actions, audit trails of every step, rules for what the AI may remember, data retention and deletion, and a named owner for each agent. Good governance should not mean a ban. It means making the approved path easy enough that teams do not reach for unapproved tools instead.

Example

For example, a store decides that its AI agents may answer customers and change subscriptions, that order cancellations need a teammate's approval, that agents may not remember customer personal details, and that the operations lead reviews agent history every Friday.

Why AI governance Matters

Clear governance lets a business use AI for real work while staying in control of risk, privacy and accountability.

AI governance FAQ

Does a small business need AI governance?

Yes, though AI governance for a small business can be short: a list of approved tools, what data they may see, which actions need approval and who checks the work.

What is the difference between AI governance and AI guardrails?

Governance is the overall set of policies and accountability. Guardrails are the specific technical limits that enforce parts of it inside an AI product.

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