Disaster recovery in AI security is critical because it ensures organizations can do what after a security incident?

Prepare for the ISACA Advanced in AI Security Management (AAISM) Test. Study with in-depth multiple choice questions, each offering insightful hints and detailed explanations. Equip yourself with expert knowledge and get exam-ready!

Multiple Choice

Disaster recovery in AI security is critical because it ensures organizations can do what after a security incident?

Maintaining operational continuity is the focus here. After a security incident, disaster recovery aims to restore and keep AI services available as quickly as possible, so the business can keep functioning with minimal downtime. This involves having backups, redundant systems, and well-practiced recovery procedures to meet targets for how quickly services are restored and how much data loss is tolerable. In an AI context, that means being able to bring back inference endpoints, data pipelines, and model artifacts with minimal interruption, preserving service availability and trust.

The other options address different goals: improving model accuracy is about performance, not resilience after an incident; reducing data collection isn’t related to recovering operations; shortening development cycles concerns project speed, not post-incident restoration.

Disaster recovery in AI security is critical because it ensures organizations can do what after a security incident?

Prepare for the ISACA Advanced in AI Security Management (AAISM) Test. Study with in-depth multiple choice questions, each offering insightful hints and detailed explanations. Equip yourself with expert knowledge and get exam-ready!

Disaster recovery in AI security is critical because it ensures organizations can do what after a security incident?

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