How do you reduce security false positives with AI?

AI technology can reduce security false positives by 70-80% through behavioral analytics and contextual awareness that static rule-based systems cannot achieve. False positives—legitimate activities incorrectly flagged as threats—create alert fatigue that overwhelms security teams, causing them to ignore or miss actual attacks buried in thousands of irrelevant warnings.

AI-powered platforms reduce security false positives through sophisticated behavioral modeling. Instead of rigid rules, machine learning algorithms learn what "normal" looks like for each user, device, and application. The AI considers multiple contextual factors simultaneously: user role and typical work patterns, time of day and access location, historical behavior and peer group norms, and data sensitivity and business impact. This contextual intelligence prevents false alarms while maintaining high detection accuracy.

Ridge IT Cyber's Microsoft 365 security implementations use Mimecast social graphing that builds detailed communication models for every employee. When business email compromise attacks occur, the AI instantly detects deviations from established baselines—catching sophisticated attacks while ignoring legitimate variations that rule-based systems would incorrectly flag.

The ability to reduce security false positives enables faster incident response. When security analysts trust that AI alerts represent genuine threats, they investigate immediately rather than dismissing notifications. Our managed detection and response services leverage AI platforms that achieve 98%+ alert accuracy, essentially eliminating alert fatigue.