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AI cybersecurity combines human and artificial intelligence for an integrated approach to threat detection and response. AI uses behavioral analytics and machine learning to monitor data and detect patterns that indicate the presence of phishing, malware, brute force login attempts, suspicious financial transactions, and more. This allows for quicker detection and response to prevent threats from spreading and causing damage.

AI cyber security automation also frees up employees’ time by automating repetitive tasks, allowing them to focus on more important and complex work. It enables a faster, more effective response to incidents by prioritizing alerts based on risk and providing context for analyzing the root cause of an incident to reduce vulnerabilities and improve future protection.

As threats evolve, AI can improve its capabilities by continually learning from data. ML algorithms enable AI to recognize patterns, establish a baseline of normal behavior, and discover anomalies in real-time. This can help identify and prevent sophisticated attacks such as spear phishing, which requires attackers to impersonate high-profile individuals like company CEOs.

However, overreliance on AI can result in errors that could impact cybersecurity systems. For example, if an AI-based solution isn’t adequately maintained and retrained, it can develop biases that affect its decision-making. It’s also important to ensure that any AI-based software is designed for explainability so that human cybersecurity experts can understand and validate results, ensuring optimal outcomes.