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AI cybersecurity is the process of using machine learning to detect and mitigate cyberthreats. It involves combining endpoint telemetry, user behavior, and network flows to create baselines of what “normal” activity looks like for each device or person in an organization. It then flags any actions that deviate from those baselines and alerts them for additional scrutiny. This helps detect zero-day or stealth attacks that typically lack signatures and can be difficult for traditional security tools to detect.

The rise of advanced persistent threats and zero-day attacks requires a new generation of defenses. These systems must be able to ingest massive volumes of data and recognize patterns of anomalous behavior, then synthesize that information into actionable insights. That’s why human security professionals are increasingly being supplemented with AI technology.

CISOs should look for an AI cybersecurity solution that is highly scalable and focuses on their biggest pain points. They should also verify that the solution covers their network, endpoints, or cloud environment and that it integrates with their existing security tools. Finally, they should choose a system that works to eliminate alert fatigue by quickly refining baseline data and re-investigating alerts to reduce false positives.

Since AI technology is evolving rapidly and has little regulation, internal governance guardrails are critical. CISOs should ask their vendors about their approach to governance, and review master service agreements. They should also look for solutions that can be easily reconfigured in case of a change in business needs or new security risks.