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AI cybersecurity applies machine learning algorithms to help identify, detect and neutralize cyberthreats before they cause significant damage. In addition to enabling advanced threat detection and response capabilities, AI cybersecurity can improve user authentication and enable automated regulatory compliance management.

AI’s ability to quickly process large volumes of data makes it ideal for vulnerability scanning and patch management tools. In these use cases, AI can scan the entire corporate environment for vulnerable software, evaluate the potential impact of a vulnerability and recommend the appropriate patch or mitigation to reduce an organization’s attack surface.

It can also be used to analyze logs and event information from security tools, such as extended detection and response (EDR/XDR) and security information and event management (SIEM) solutions. This helps to identify patterns of behavior that could be indicative of a cyberattack, such as abnormal traffic flows or changes in network or device activity. In the case of XDR and SIEM, AI can also be used to prioritize events for security teams to investigate based on their impact.

However, for organizations to gain the full benefits of AI, it must be designed, deployed and operated securely. The NCSC has published a series of guidelines that can help data scientists, developers, decision-makers and risk owners build secure AI systems. These include ensuring that AI is properly vetted and approved by the business, and that the system functions as intended without exposing sensitive information to unauthorised parties.