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Artificial intelligence (AI) can be used to detect and neutralize cyber threats. It acts as a force multiplier for seasoned cybersecurity professionals by monitoring vast swaths of data, detecting nuanced adversarial attacks and enhancing threat hunting and risk assessment capabilities. As the cyber landscape becomes increasingly complex, incorporating AI into your defenses is essential to ensure that you stay secure now and in the future.

Unfortunately, not all AI is created equal. The recent emergence of generative AI models and large language models has thrust AI into the public spotlight, giving criminals, hackers and nation states powerful tools they didn’t have before. This includes the ability to spoof an individual’s voice or video image, creating a virtual copy of a person to steal private information, commit fraud or take down websites and networks.

These sophisticated techniques can have major long-term consequences, such as revenue loss, productivity disruption and reputation damage. Suboptimal AI security can also compromise your crown jewels and add you to the list of data breach victims.

The best way to protect your organization from these threats is to follow all of the best practices for software maintenance. This includes regularly updating the AI software and frameworks you use, keeping up with OS updates and implementing firewalls, intrusion detection systems and backup technology. Additionally, a key step is to implement adversarial training to strengthen AI models’ resilience against attack. This is an advanced machine learning method that improves AI’s defenses by exposing it to different scenarios, data and attacks.