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AI cybersecurity is a growing area of interest for many companies. However, introducing these tools requires careful planning to ensure that employees use them securely, responsibly and in compliance with company policies. Moreover, organizations must understand the risks associated with generative AI so they can be proactive in mitigating them.

The NCSC published a set of guidelines to help data scientists, developers and decision-makers build AI systems that work as intended, are available when needed, and don’t expose sensitive information to unauthorized parties. The guidelines also include a set of best practices for security teams to consider when deploying AI.

Cybercriminals are using more advanced attack vectors, bypassing traditional file-scanning and signature-based antivirus protections. This is where AI-based approaches are useful, as malware needs to exhibit specific behaviors to be detected. AI tools can quickly analyze data and identify suspicious behavior to detect cyberattacks that would otherwise go unnoticed.

As an additional layer of defense, AI can reduce the time it takes to respond to a cyberattack and mitigate the damage done by automating some steps in the response process. This frees up security operations team members to focus on the most important threats, as well as improve incident response times and security posture overall.

When selecting an AI cybersecurity solution, look for one that provides seamless integration with existing security infrastructure and tools, such as XDR or SIEM. Make sure the scope of coverage is aligned with your organization’s biggest security pain points to avoid gaps or blind spots in threat visibility. And, for ease of deployment, find out whether the vendor supports APIs and pre-built connectors to existing platforms, such as firewalls or identity providers.