AI Governance Lifecycle
The AIGO AI Governance Lifecycle describes how governance activities operate throughout the life of an AI system.Purpose
AI governance is not a one-time assessment. Governance activities continue as an AI system is designed, developed, deployed, operated, changed, monitored, and eventually retired. The lifecycle provides a structured way to manage those activities continuously.Lifecycle perspective
The lifecycle connects governance activities such as:- system registration
- classification
- risk assessment
- control implementation
- approval
- deployment
- monitoring
- assurance
- change management
- incident management
- improvement
- retirement
Continuous governance
Lifecycle governance should be revisited when material changes occur. Examples include:- significant system changes
- changes in intended use
- changes in risk
- new incidents
- changes in applicable requirements
- material changes in operating conditions
Relationship to other AIGO components
The lifecycle provides the operational flow through which the rest of the framework is applied. It connects: governance domains → roles → risk → controls → evidence → assurance → improvementSource
The canonical lifecycle document is maintained in:framework/05-lifecycle/AIGO-AI-Governance-Lifecycle-v0.1.md
The GitHub repository is the authoritative source for the complete v0.1 lifecycle model.