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AI technology is playing a key role in cybersecurity, delivering advanced capabilities to prevent threats from entering and destroying systems. Cybersecurity companies are using the technology to improve threat detection and response, provide better user experience, and automate security operations.

In addition, the technology helps protect against emerging threats that traditional software signature-based methods may not pick up. This includes the ability to detect malware from its behavior, not just its code, and to automatically block zero-day malware without a specific signature. It also enables protection to work offline, on IoT devices and mobile phones, and in the cloud, without requiring connectivity.

However, if the AI cybersecurity solution fails to properly mask and encrypt sensitive data, it can lead to data breaches and privacy issues. Moreover, if the data is used to train the AI model but not for real world analysis and testing, it can result in false positives. This can give malicious actors a false sense of security, and they can target your organization with sophisticated attacks.

Identifying and responding to cyberattacks in real-time is crucial to reducing their damage. This is where AI for cybersecurity can help, as it identifies and responds to anomalies and deviations from typical behaviors more quickly than human security professionals can.

In addition, it helps improve threat detection and response by collecting and analyzing massive amounts of data, and providing insights for quicker and more effective decision-making. This allows security personnel to prioritize alerts and surface root causes for vulnerabilities, which can ultimately reduce incident response times. UK-based Darktrace, for example, uses self-learning AI to detect and combat a range of cyberthreats across networks, IoT and cloud environments.