When a model is updated, the API version should change to prevent consumers from unknowingly receiving outputs from a different model version. API versioning ensures that consumers can pin to a specific version and receive consistent behaviour until they explicitly migrate to a newer version.

Deprecated API versions are retired on a documented schedule, with consumers notified in advance. The notification period should be sufficient for consumers to test and migrate to the new version. For deployers of high-risk AI systems, migration to a new API version may require the deployer to update their own documentation and processes; the deprecation timeline should account for this.

The API versioning scheme, the deprecation policy, and the notification process are documented in Module 3 (as part of the system’s architectural specification) and Module 9 (as the change may affect security properties). Each API version change is recorded in the deployment ledger.

Key outputs

• API version changes aligned with model updates
• Documented deprecation policy with consumer notification timeline
• Deployment ledger entries for API version changes
• Module 3 and Module 9 AISDP documentation