This paper highlights how AI-driven auditing enhances static application security testing (SAST). Page 1 explains that manual triage is slow and error-prone, leading to developer fatigue. AI auditing uses ML models trained on expert-reviewed findings to reduce false positives, accelerate prioritization, and provide more accurate root-cause insights. Visuals show side-by-side comparisons of traditional vs. AI-assisted workflows. The paper details integration into CI/CD pipelines, improved remediation guidance, and measurable ROI through faster scans and reduced noise. It positions AI auditing as essential for modern AppSec programs.

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