Which of the following is a use case of AI-driven incident response?

• A. Detection and alerting, root cause analysis, incident resolution, and post-incident analysis.
• B. Data backup scheduling and retention.
• C. Policy drafting and onboarding.
• D. Network equipment procurement.

Answer: (A)

AI-driven incident response centers on handling security events from detection through learning after the event, using automation and intelligent analysis to speed up and improve each step. The strongest use case combines detection and alerting with root cause analysis, incident resolution, and post-incident analysis because AI can continuously correlate signals from multiple sources, identify the underlying cause, guide or automate containment and remediation, and generate insights that inform stronger defenses for the future. This end-to-end capability reduces mean time to detect and resolve incidents and produces actionable post-incident learnings.

The other options describe routine IT tasks that don’t involve the security incident response lifecycle. Data backup scheduling and retention is about protecting data availability, not diagnosing or responding to security events. Policy drafting and onboarding relates to governance and human resources processes, not incident handling. Network equipment procurement is about asset management and planning, not detecting or resolving incidents.