Two sentences summarize the shift from pre-trained AI-SOC to continuously learning, analyst-driven AI that evolves with local context. The article outlines how feedback loops, transparency, usability, and measurable metrics transform SOCs into adaptive, explainable systems that reduce false positives and improve detection and response.
#ShaharBenHador #RadiantSecurity
#ShaharBenHador #RadiantSecurity
Keypoints
- Pre-trained AI-SOC models rely on historical data and may misclassify travel or context-specific behavior.
- Continuous learning uses analyst feedback to adapt detections to the organization’s environment.
- Effective feedback loops require visible reasoning and measurable improvements to sustain analyst engagement.
- A usable, integrated feedback workflow reduces false positives and aligns AI with real workflows.
- Day-90 metrics show substantial false-positive reductions, time savings, faster investigations, and higher automation coverage.
Read More: https://thehackernews.com/expert-insights/2025/11/continuous-feedback-loops-why-training.html