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As cybercriminals adapt their tactics, organizations need to evolve their defenses. AI cybersecurity uses machine learning to enhance and strengthen all aspects of security, from threat detection to prevention and response.

The most effective security AI tools work with and support human analysts, rather than replace them. They’re designed to automate repetitive tasks, increase the signal-to-noise ratio of tools like extended detection and response (XDR) platforms, provide valuable context to alerts, prioritize threats, and more—all while freeing human teams up for high-impact activities like threat hunting and incident response.

Detect & Prevent Breaches

By continuously monitoring all activity across the organization, generative AI can help security teams spot suspicious patterns and indicators of compromise. These alerts can then be fed into machine learning models to strengthen threat detection capabilities and keep the organization ahead of cybercriminals.

Analyze User Authentication Data

AI tools can assess risk factors like device, location, and time of day to determine whether someone’s login or access request is safe in real-time. This helps protect against attacks that rely on stolen credentials and overly broad permissions, while also strengthening identity and access management (IAM) systems by preventing users from keeping unneeded access privileges after they’ve left the organization.

Ensure that employees understand your organization’s policies about using generative AI tools, such as avoiding pasting confidential and sensitive data into prompts, to mitigate risks of these technologies being used by malicious actors. Also, make sure that AI tools are integrated seamlessly with existing systems to avoid siloing and improve visibility across the entire digital estate.