3 Ways AI Can Boost Your Cybersecurity

Way back when, in my IT days, keeping IT systems secure was relatively simple: setting up firewalls on Internet-facing servers, having a decent password policy, and instructing users to not download email attachments they weren’t expecting (still an ongoing battle), was most of the work.

In that era, most environments were walled gardens with few connections to the outside world. The “cloud” barely existed, and there was no “Internet of Things”. 

Oh, what a difference two decades make.

Now, everything is connected to everything else. New threats pop up constantly, attackers move faster than ever, and even well-managed environments can be blindsided by zero-day attacks or polished, professional phishing attempts. 

Clearly, more help is needed to handle this exponentially bigger attack surface. That’s where artificial intelligence (AI) is changing the game—helping IT teams stay ahead, instead of constantly reacting.

But it’s not just about “using AI.” The real power comes from how you use it. Here are three practical, actionable ways to make AI your ally in securing your IT infrastructure.

1. Automate Threat Detection and Response

AI-driven security platforms can process huge volumes of data—logs, alerts, network traffic—and spot patterns that humans might miss. But too often, admins set them up and forget them, assuming the system will just take care of everything.

Bad idea. Instead, use AI to automate your response workflows. For example, if your AI-based intrusion detection system flags an unusual login from a foreign IP, you can create an automated policy that temporarily locks the account, alerts the user, and requires multi-factor re-validation.

New AI cybersecurity tools make this possible without needing a full security operations center (SOC). Configure them to take small, controlled actions automatically—things like quarantining suspicious files or blocking IP addresses—before you even log in.

Pro Tip: Start small. Pick one or two common incidents, such as failed login storms or lateral movement detection, and let your AI system handle those automatically. Once you’re confident in its accuracy, expand from there.

2. Improve Patch and Vulnerability Management

Most breaches exploit known vulnerabilities—existing stuff that could’ve been fixed if patches were applied sooner. The challenge is knowing what to patch first. That’s where AI can save a lot of time and migraines.

Modern vulnerability management tools now use AI to prioritize patching based on real-world threat intelligence. Instead of dumping a list of 500 vulnerabilities on your lap, they rank them by likelihood of exploitation and potential impact on your environment.

Integrate these AI tools with your ticketing or workflow systems. That way, critical vulnerabilities automatically become high-priority tickets, assigned to the right teams, with deadlines and status tracking.

Pro Tip: Use AI-based analytics to predict which systems are at the highest risk based on behavior trends. Examples could be servers that handle sensitive data or see heavy external traffic. By patching those first, you drastically reduce your attack surface without overwhelming your staff. (It also cuts down on alert fatigue).

3. Continuously Monitor Users and Networks

Even the best security setups can be undone by one careless click or credential leak. AI-powered behavior analytics can help spot those problems early—often before they escalate.

By learning what “normal” looks like across your users and devices, AI can flag anomalies in real time. Maybe a user suddenly starts downloading large volumes of data after hours, or a device begins communicating with a suspicious external IP. Those red flags can trigger alerts or even automated containment using agentic AI.

Pro Tip: Enable user and entity behavior analytics wherever possible—within your SIEM, cloud management console, or endpoint tools. Set clear escalation rules for what happens when AI detects something abnormal. This includes specific detail on who gets notified, what actions are taken, and how incidents are logged.

These AI insights can also be used to train your users. For example, if phishing simulations show that certain departments click more often, AI-generated reporting can help you target awareness training where it’s needed most.

Stay Active for Your Cybersecurity Health

AI won’t replace your security team—but it can make them far more effective. The key is to actively use it: automate routine responses, focus patching on the biggest risks, and continuously monitor for unusual activity.

Of course, it’s prudent to remember that the Bad Guys also have access to AI, and they’re taking full advantage of it. You should, too. If you’re not at least testing AI in (non-production) environments, you’re falling behind—but the Bad Guys are not. They’re using it right now, and they’re looking for you.