If disabled because of an incident, can your solution's AI features be re-enabled in a timely manner?
Explanation
Guidance
Looking for incident response procedure for shutting down and re-enabling model features due to a security event. Please provide the amount of time it would take to renable your solution's AI feature(s).
Example Responses
Example Response 1
Yes, our AI features can be re-enabled in a timely manner following an incident We have documented procedures for both disabling and re-enabling our AI systems as part of our incident response plan The re-enabling process involves a security validation check, system integrity verification, and a phased restoration approach Typically, our AI features can be restored within 4 hours of incident resolution This timeline has been verified through our quarterly disaster recovery testing During the outage, we maintain business continuity through fallback to non-AI processing methods that, while less efficient, ensure critical operations continue.
Example Response 2
Yes, our solution's AI features can be rapidly re-enabled following an incident We utilize a containerized architecture with immutable infrastructure, allowing us to redeploy clean AI components from verified images within 30 minutes Our incident response team follows a documented checklist that includes security validation before re-enabling services The process is fully automated through our CI/CD pipeline and has been successfully tested during our monthly disaster recovery exercises Additionally, we maintain redundant AI processing capabilities in a separate environment that can be activated within 15 minutes if the primary environment requires extended remediation.
Example Response 3
No, our current implementation does not support rapid re-enabling of AI features following an incident If our AI components need to be disabled due to a security event, the restoration process would require manual intervention by our development team and could take 2-3 business days to complete This is because our AI models require extensive retraining and validation before being returned to production We recognize this as a gap in our incident response capabilities and are currently developing an improved architecture with containerization and automated deployment that will reduce restoration time to under 4 hours This enhancement is scheduled for completion in Q3 of this year.
Context
- Tab
- AI
- Category
- AI Policy

