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CISOs need to understand the benefits and risks of AI cybersecurity. AI enhances cybersecurity capabilities and helps teams prioritize alerts, speed incident response, and identify underlying issues to reduce vulnerability risk. But, like any technology, it can be exploited by bad actors. Consequently, organizations must build a resilient cyber strategy to protect against attacks that target and compromise AI systems.

Using machine learning algorithms, an AI cybersecurity system understands “normal” user behavior and detects deviations that may indicate a malicious attack. This type of threat detection is called behavioral analytics.

AI cybersecurity tools also use generative techniques, which automatically synthesize data into human-readable reports and presentations that help analysts quickly understand what’s happening, in natural language or by generating diagrams. These capabilities improve security incident response time by removing the need for manual, repetitive tasks and enhancing the ability to scale, reducing human error and increasing efficiency.

Another advantage of AI cybersecurity solutions is that they provide automated, continuous protection to thwart cyberattacks before they become an issue. This enables them to reduce the time between detection and response, significantly reducing the potential impacts of a breach.

Unlike traditional security defenses, which are based on attack signatures and indicators of compromise (IOCs), an AI cybersecurity solution uses behavioral analytics to detect threats that evade existing technologies by mimicking legitimate user behavior. This enables them to better prevent more advanced attacks such as spear-phishing, where attackers impersonate high-profile executives to gain access to sensitive information and systems.