Security teams managing cloud‑native workloads face an overwhelming volume of alerts, logs, and configuration changes, making manual triage unsustainable. AI‑assisted security operations platforms leverage machine learning to analyze telemetry from cloud infrastructures, Kubernetes clusters, containers, and serverless functions, building behavioral baselines for normal activity. When anomalies occur—such as unusual API spikes, lateral movement, or configuration drift—AI models prioritize incidents by risk and business impact, surfacing only the most critical issues. Generative AI then helps analysts by summarizing incidents, enriching tickets with contextual data, and suggesting response playbooks, dramatically reducing mean time to detect and mean time to respond. Integrated with SIEM, SOAR, and EDR tools, these AI‑augmented workflows enable 24×7 security operations even amid talent shortages, turning reactive alerts into proactive defense.