Information Security Analysts

In cybersecurity, many routine security checks are already AI-driven. For example, antivirus and endpoint tools use machine learning to scan for new viruses and abnormal behavior around the clock. Microsoft’s AI-powered Defender system famously detected a complex ransomware attack by spotting unusual activity faster than humans could ^[1].

Industry experts note that up to half of basic security tasks (like scanning logs and updates) could be automated ^[2]. An ISACA report explains that “AI algorithms can be used for…intricate threat detection, anomaly identification,” and even automate parts of incident response ^[3]. In practice, software now auto-runs virus reports, checks network traffic, and flags risks 24/7.

However, work that needs human judgment or communication is still done by people. Writing detailed security policies, explaining rules to coworkers, and handling violations require empathy and context. In other words, AI tools act like helpers or “copilots,” handling repetitive checks so analysts have time for the hard puzzles ^{[2] [3]}.

Why hire AI or not? One factor is availability: many security products today come with built-in AI. In fact, a survey of security leaders found 55% plan to invest in AI for their operations (and 88% in cloud tools) ^[2].

AI can speed up detection and cut breach losses, which is a big economic benefit. On the other hand, new AI systems can be costly to buy and tune. Sometimes it’s cheaper to hire people, especially for smaller companies.

Labor conditions matter too: there is a cybersecurity talent shortage (about 32% of teams say they lack needed skills ^[2]), so AI is one way to help overworked teams. Finally, social and legal factors make adoption cautious. Security breaches are serious, so firms usually keep a human “in the loop.” Most experts agree that although AI will grow in security, human skills – like creative problem solving and communication – remain essential for the job ^{[2] [3]}.