Which term best describes using automated analytics, NLP, and predictive capabilities to accelerate threat detection and SOC tasks?

• A. APIs
• B. AI
• C. Beacons
• D. SOAR

Answer: (B)

Applying artificial intelligence to security operations means using systems that learn from data, interpret human language, and forecast likely threats to speed up detection and response. When you bring automated analytics, natural language processing, and predictive capabilities together, you’re leveraging AI to sift through vast security telemetry, extract meaning from unstructured text like incident notes or threat reports, and anticipate which signals matter most. This leads to faster triage, smarter alert prioritization, and proactive defense, helping analysts focus on the most significant risks.

APIs are just interfaces for accessing and exchanging data between tools; they enable integration but don’t inherently perform analytics or predictions. Beacons refer to signals or indicators, not a technology approach for driving analytics and decisions. SOAR focuses on automating and orchestrating response workflows; it improves efficiency of playbooks and collaboration but doesn’t by itself embody the NLP and predictive analytics described here.