AI Driven Threat Detection - Wisconsin Bankers Association

By Rob Foxx

Have you ever wondered why there’s been such a strong push toward next-generation antivirus (NGAV) programs over the past five years? Many individuals, businesses, and even banks often fail to see the value in upgrading their traditional antivirus solutions. The reason isn’t always a lack of need — it’s often a lack of clear communication. As someone in IT, I admit that we’re not always the best at explaining complex concepts to those outside the tech world.

For years, traditional antivirus products rarely found any real issues — and if they did, the problems were usually resolved quickly. But does that really mean you’re safe?

Traditional antivirus is primarily designed to detect file-based threats. If an attacker is using only known malicious files, there’s a good chance your antivirus will catch it. However, attack tactics have evolved. A small change to a file can alter its signature and bypass detection. Worse, many modern attacks don’t rely on malicious files at all.

Today’s threats often reside in active memory or use legitimate system tools already present on the machine—a method known as “living off the land.” These attacks can operate under the same permissions as the user, making them harder to spot. In some cases, the attack originates from another compromised device on the network, meaning the affected machine may not have done anything wrong. While not all of these attacks use AI, the most advanced and damaging ones often do.

So, how do we defend against them?

That’s where AI-powered antivirus tools with EDR (Endpoint Detection and Response) capabilities come in.

Unlike traditional antivirus, AI-based systems use deep learning to monitor behaviors — not just file signatures. These tools analyze endpoint behavior, user behavior, network traffic, and file activity to identify suspicious actions. They go beyond detecting “known threats” by recognizing behavior that resembles malicious activity. Depending on configuration, these systems can automatically remediate issues or flag them for investigation.

Of course, behavior-based detection isn’t perfect. False positives are a reality. Fortunately, most systems allow tuning through rules, whitelists, and baselines to distinguish between real threats and benign activity.

EDR platforms also offer other advantages. For example, is one of your salespeople logging in at 3:00 AM on a Saturday? That could be a legitimate case — or it could be a compromised account. Did someone plug in a USB device? That might be a new keyboard — or it might be an external drive loaded with malware. Is your backup system suddenly seeing a spike in traffic? That could signal a ransomware attack preparing to encrypt your backup data.

With the right tools, you can detect and respond to threats like these before they cause damage. Which tools are best? That depends on your environment, but some leading names in that space include Cynet 360, CrowdStrike, SentinelOne, and others. Most rely on similar data sets, but their features, interfaces, and response strategies can vary.

In today’s cyber landscape, traditional antivirus simply isn’t enough. AI-powered, behavior-focused tools are no longer optional — they’re essential.