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As AI moves into the enterprise, IT teams are looking for ways to deploy and use it effectively while mitigating risks. A strong understanding of the core principles of AI security can help teams adopt, deploy and integrate this technology.

This category includes AI security platforms that apply artificial intelligence to identify, prioritize and remediate cybersecurity risks across applications, cloud infrastructure and development workflows. They provide a range of capabilities, including AI-powered code review and IDE integrations for safer coding practices, intelligent triage and automation, one-click AutoFix and autonomous AI pentesting. They also enable centralized management and integration of AI-powered risk detection, response and governance into broader security portfolios. Unlike traditional tools that rely on signatures and rules, AI-driven systems reduce false positives and focus teams on real, exploitable issues with context-aware analysis. This helps them scale with modern cloud-native development and provide end-to-end visibility and protection for code, dependencies, APIs and runtime environments without slowing down delivery. They also improve signal quality by learning what normal behavior looks like in specific environments, enabling them to identify threats that other systems miss.