AI
AI Governance
Industrial AI needs boundaries before scale.
What this topic covers
What practical AI governance should resolve.
Governance should define what the system can see, what it can do, when it must stop and who remains accountable.
- Approved information sources, permissions and data-access boundaries.
- Allowed actions, review points and escalation conditions for bounded agents and workflows.
- Traceability of model outputs, source context and consequential actions.
- Controls for uncertainty, missing context, conflicting evidence and human override.
Governance is not a layer added after deployment. It is part of the engineering definition of an AI-enabled workflow.
Use the technical topic to sharpen the question, then bring the operating condition when the problem needs execution.