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AI cybersecurity combines advanced machine learning with security solutions to detect and respond to cyber threats. This approach improves on the effectiveness of traditional methods and enables organizations to reduce risks, save costs, and protect data, systems, and people faster than human cyber teams can on their own.

Using AI to detect and stop threats like malware, ransomware, and phishing attacks allows enterprises to keep their employees, customers, and partners safe online while remaining competitive. AI solutions provide protection even if threat signatures haven’t been updated promptly and prevent threats from bypassing other defenses by identifying risky behavior based on patterns, rather than looking for specific code in an image or file.

AI is particularly useful for detecting new types of threats because it can learn from previous activities to identify patterns. It uses history to build profiles on users, assets and networks, so it can quickly detect deviations from normal behaviors and take automated actions. This helps organizations protect against malware and other cyber attacks that use the latest exploits and techniques to evade detection by conventional software and systems.

However, implementing AI for cybersecurity must be done carefully. For example, selecting a solution with an automated self-learning algorithm that constantly retrains itself to adapt and recognize new threats is important. It is also important that the AI solution fits well with an organization’s existing security architecture. If the AI is not integrated with a Zero Trust framework, for instance, it won’t be effective.