Missio Systems public knowledge
AI governance framework
An operating framework for accountable AI decisions, proportionate controls, evidence, monitoring, escalation, and continual improvement.
Last reviewed:
Direct answer
AI governance should help the organization make better decisions at the speed its risk permits. It connects portfolio scope, accountable ownership, decision rights, risk classification, controls, evidence, monitoring, incidents, and oversight.
Six operating elements
- Scope the systems, uses, actors, jurisdictions, and material decisions.
- Assign accountable owners and explicit approval, challenge, pause, and retirement rights.
- Classify risk and value using context, impact, autonomy, data, and dependency.
- Apply proportionate controls across acquisition, development, testing, release, use, and change.
- Maintain evidence that supports claims, approvals, monitoring, exceptions, and incidents.
- Review performance and risk, correct weaknesses, and improve the system.
The framework is effective when evidence changes decisions, not merely when documents exist.
Source boundary
This is original Missio operating guidance informed by the cited sources. It
is not an official implementation guide, certification claim, or copied
standard.