Look at the spec sheet for almost any modern security product and you’ll likely see the phrase “AI-powered.” AI is used to automate repetitive tasks, speed up responses, and help detect threats that traditional tools might miss or struggle to understand.
AI’s basic mode uses unsupervised or supervised machine learning (ML) to spot patterns and make predictions using large data sets. One step up from this is deep learning (DL), a more advanced neural network model in which the output from one learning stage is used as input for a new stage.
This is the level at which artificial intelligence for cyber security is being deployed. It is designed to work at scale and requires less human input.
AI is now central to automating threat detection, incident response, and even generating easy-to-understand incident summaries for security teams and executives. Microsoft highlights that AI-driven security tools can identify malware, detect intrusions, and reduce false positives, allowing businesses to respond to threats more quickly and efficiently.
In 2025, ‘Agentic AI’ or autonomous security agents are being used to triage alerts and remediate vulnerabilities with minimal human intervention, marking a shift towards more proactive, AI-driven cyber defence.
However, while AI is now central to many security operations, businesses still rely on a mix of traditional and AI-driven techniques.