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AI cybersecurity leverages artificial intelligence to protect your organization from cyberthreats and make your team more efficient. It automates routine tasks like monitoring and scanning, allowing your team to focus on high-level problem-solving and strategic decision-making.

It improves security posture by detecting and blocking sophisticated threats. It strengthens identity and access management by monitoring user login behavior, device characteristics and other patterns to detect illegitimate account takeover attacks and identify stolen credentials. It helps prevent data leaks by identifying sensitive information in unstructured data and encrypting it before it leaves the company network, or by leveraging machine learning to automatically update and improve existing policies.

AI tools can reduce risk by automatically updating and analyzing new threat trends, and by identifying patterns in your attack surface that are harder to see with traditional solutions. However, the accuracy of AI can depend on the quality and integrity of the data used to train and operate it, so you need to put processes in place to prevent tampering or other forms of adversarial attack. It’s also important to ensure that you can explain the reasoning behind AI decisions, fostering trust, accountability and smarter human oversight.

Some AI cybersecurity solutions can be integrated into your existing tools and infrastructure, such as XDR or SIEM platforms. For example, Microsoft Security Copilot connects with your existing security products to prioritize alerts and synthesizes the results into actionable insights that your team can act on. Other solutions, such as Pixeebot, work as an automated product security engineer that seamlessly integrates into developers’ workflows to improve code security without disrupting productivity.