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AI is reshaping cybersecurity by streamlining routine tasks, reducing human error, and automating threat detection. But it’s also transforming the way companies fight back against cyberattacks by leveraging advanced analytics to spot patterns and trends that humans may miss.

Detection – AI watches for abnormal behavior, like suspicious login attempts or out-of-the-ordinary network traffic patterns, and spots potential threats based on the context, environment, and other attributes of systems, endpoints, and identities. It then analyzes this data to determine if an attack is occurring and how serious it might be. If it is, it takes action by limiting access or removing unauthorized users from systems, or by providing alerts to security teams for rapid response and remediation.

Analysis – AI uses machine learning to build comprehensive security information from disparate data sources. It can detect subtle anomalies, evaluate files for malicious processes, and cross-reference alerts from different tools into a single incident view. These actions reduce alert fatigue and speed up investigations.

Threat Prioritization – An AI-powered EDR can automatically classify and prioritize incidents based on their risk to your business, including ransomware, exploits, and other types of attacks. It can also identify the tools and IP addresses used by a threat actor, and link them to past incidents.

When evaluating an AI cybersecurity tool, consider how well it fits your organizational security goals and operational needs. For example, ask the vendor to support a Proof of Concept (PoC) to ensure the tool can handle your unique systems, applications, and threat landscape. It should also be able to integrate with your existing technology stack and easily scale with your growth.