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The National Cyber Security Center (NCSC) wants everyone to benefit from AI, but there are important security implications that need to be considered before deploying any type of AI cybersecurity tool. This guide covers the key considerations for CISOs to keep in mind when evaluating AI tools to safeguard their organisation’s assets.

AI cybersecurity uses machine learning to analyze massive volumes of data and identify patterns that indicate threats. It provides the intelligence to detect and respond to threats with speed and scale that human defenders can’t match. AI can sift through billions of network requests, endpoint activities, user behaviors and data points daily to quickly scan for attacks and other threats. This can also reduce the number of false positives, which can be overwhelming for security teams.

ML models use pattern recognition to identify anomalies and potential threats, such as malware infections or unauthorized access attempts. In addition, they can help detect and resolve vulnerabilities faster, automate tedious tasks, and improve overall system health and performance.

However, AI in cybersecurity is also being weaponized by malicious actors to create advanced threats that can penetrate existing defenses. As a result, cybercriminals continue to adapt their tactics, and it is crucial for organizations to have extra layers of defenses in place, especially when dealing with adversarial AI attacks.

Using AI in cybersecurity helps protect against these evolving attacks, while providing the agility to defend against threats of all kinds. When selecting an AI cybersecurity tool, carefully evaluate the algorithms, integration capabilities and real-world performance to ensure it’s able to meet your organisation’s security goals and operational needs.