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AI cybersecurity uses machine learning to protect systems against phishing attacks, ransomware, spoofed websites and other malware. It can detect patterns in users’ behavior that might indicate a cyberattack and help security teams to take quick action before attackers do significant damage.

AI’s ability to work around the clock and provide continuous monitoring can help reduce the chances of a data breach. It can also help to speed up response times and reduce the cost of a cybersecurity incident.

Its scalability allows it to analyze large volumes of network traffic logs, system logs, user behaviors and threat intelligence feeds to identify threats more efficiently than human analysts can. It can also automate tasks such as alert aggregation and sorting, which improves efficiency and reduces human error.

It can help detect more advanced or emerging cyberattacks. Supervised AI models use labeled and classified data to learn what normal behavior looks like, and can then detect when a new activity doesn’t match the norm. Unsupervised AI models use a different approach, by using natural language to describe a situation and then identifying patterns in the data that suggest an event or attack.

It can detect insider threats and prevent them from stealing company data, intellectual property, sensitive information or other valuable assets. It can also stop employees from accessing confidential information via their personal devices or accounts. This can minimize the risk of breaches and improve employee productivity. It can also help companies comply with regulatory frameworks such as GDPR.