Cybersecurity has become a domain where AI is used on both sides of the conflict: defenders use it to detect and respond to threats faster, while attackers increasingly use it to craft more convincing attacks.
Threat Detection
AI models trained on network traffic patterns can flag unusual activity that may indicate an intrusion, often catching subtle anomalies that would be extremely difficult for a human analyst to spot manually across the sheer volume of daily network traffic.
Phishing Detection
AI-powered email security tools analyse the language, sender patterns, and links within messages to identify likely phishing attempts, adapting more quickly to new attack patterns than static blocklists.
The Other Side: AI-Assisted Attacks
Unfortunately, the same generative AI tools that help write emails can also help attackers craft more convincing phishing messages, and AI can be used to automate parts of the reconnaissance and attack process, creating an ongoing back-and-forth between attackers and defenders.
Because of this dynamic, cybersecurity teams generally treat AI as one layer of a broader defence strategy, combining automated detection with strong fundamentals like software updates, staff training, and multi-factor authentication rather than relying on AI alone.