Glossary
AI Governance
AI governance is the set of policies and mechanisms that decide what the system is allowed to do, what needs human approval, and how every decision stays reviewable. Without it, organizational use of agentic systems cannot be justified.
Also called حاکمیت هوش مصنوعی
“What if it is wrong?” is the right question, and the answer should not be “it is not wrong.” The right answer is an explanation of the control mechanism.
Effective governance usually has four parts. **Policy check before execution:** every sensitive action is tested against a set of rules and, if rejected, stays stopped. **Human approval:** actions with an external effect require a named person’s approval. **Traceability:** every decision can be followed back to its evidence. **Autonomy ladder:** the level of authority rises gradually, based on recorded performance.
An important implementation point: the governance layer must be deterministic, not language-model-based. A rule that can itself be misinterpreted is not a rule.
Common questions
- Which actions should require human approval?
- Any action with an external effect: contacting a customer, changing an order, a financial commitment, or any change that is costly to reverse.
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