When it comes to AI and security, I see two failure modes. Most people only worry about one of them.
Failure mode 1: moving too fast and exposing sensitive data.
Failure mode 2: locking everything down so tightly that your organization can’t experiment, can’t learn, and falls behind while everyone else figures this out. That’s just as dangerous - and I’d bet it’s more common.
What actually works is a risk-based security model. It’s not a new concept - regulated industries have used it for decades. The question isn’t “is there any risk?” It’s “what happens if this information gets out, and is that an acceptable risk given what we gain?”
Some information costs you the company if it leaks. Treat it accordingly.
Some information, if it escaped, amounts to a bad day on social media. That risk profile is very different.
You don’t need the same security posture for both.
The goal is to find the space where your team can actually experiment - ideally with sample data, not live customer data - so you build the organizational muscle to work with AI safely before the stakes are high.
Innovation requires some room to move. A smart risk model gives you that room.