Why AI Security Risk Needs a More Proactive Strategy

AI security needs an earlier, more deliberate strategy because organizations are adopting powerful systems faster than their governance and defensive controls can mature. Attackers abusing AI are only part of the problem. A poorly managed rollout can open new internal exposure long before anything visibly breaks.

That makes AI security a leadership and operating-model issue as much as a technical one. Teams that want to move fast without piling up risk need clear rules for data use and model access. Testing and human review belong in the same rulebook.

AI cuts both ways

Artificial intelligence makes many tasks faster and cheaper. The same capability helps attackers find and exploit weaknesses. Dr. Chase Cunningham, the security strategist best known for his work on zero trust, describes AI as both a tool for strengthening defenses and a new way in for attackers.

His view is that the risks of dual-use technology can be managed without stopping progress. Doing that means understanding where AI helps and where it adds exposure.

Building security in early

Cunningham argues that waiting to react to AI threats is not enough. Security has to be part of AI projects from the first design decisions, so the resulting systems hold up under attack.

He also calls for cooperation. AI risks cross borders and industries, so he wants governments and companies to share what they learn, with universities in the loop.

Rules written for AI

Cunningham’s work points toward security frameworks written specifically for AI, with guidelines that cover how models are trained and deployed. They need to be flexible enough to keep up with the technology. They also need to be firm enough to mean something.

Education is another part of his work. He wants practitioners, and the next generation entering the field, to understand how AI changes the risks they manage.

Practical steps for security leaders

Cunningham’s message comes down to three things. Treat AI as dual-use. Build controls in from the start. Work with others instead of alone.

For security leaders, a sensible start is an inventory of every AI tool in use, who approved it and what data it can reach. Then set rules for model access and human review before the next deployment.

Dan Evert, CCNP

Dan Evert is a self proclaimed Router Jockey. Dan got heavily involved in networking right out of high school and has never looked back! Dan is giving back by working with high school students to get them involved and interested in Networking and Security.