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The challenge of safeguarding data, managing user access and detecting and responding to security threats has never been more complex. Today’s cyberattackers are more sophisticated, an attack surface is expanding exponentially and infrastructure complexity is increasing, making it difficult for teams to keep pace with new threats. AI cybersecurity solutions optimize analysts’ time by accelerating threat detection, expediting responses and protecting data and user identity. While enhancing the human element, they also allow teams to remain in the loop and in charge.

With its inherent scalability, AI excels at handling massive volumes of data to analyze network requests and logs, endpoint activity, user behavior and intelligence feeds in real-time, providing an effective defense against emerging threats. In addition, AI models continuously learn and adapt so they can quickly recognize anomalous behavior that may escape traditional file-scanning and signature-based approaches.

But, the use of AI in cybersecurity raises concerns around data privacy and if not designed properly could be vulnerable to hackers who gain access to the training data for AI systems. The lack of skilled professionals is another barrier to deploying AI systems. And, it can be expensive to implement AI-based cybersecurity tools if organizations don’t have the necessary hardware or cloud resources.

People who have skills in both AI and cybersecurity are in high demand as they can help bridge the gap between the two technologies. These individuals are needed to develop AI cybersecurity applications that can protect against advanced threats. They need to understand machine learning data modeling, deep neural networks and language modeling, as well as the principles of cybersecurity.