As AI moves from experiments to systems that touch real data and take real actions, security stops being optional. The good news: AI security comes down to a handful of clear principles, applied consistently. Here’s the practical guide, and how dgm builds it in. (dgm implements osFoundry, a separate company’s platform — we are not osFoundry.)

The core idea: control

AI security is fundamentally about control — what data AI can access, what it’s allowed to do, where your data goes, and who’s accountable. Get those under control and most risks are managed; leave them loose and you’ve created exposure.

The best practices

  • Least-privilege data access. AI reaches only the data it needs for its task — not everything by default.
  • Action boundaries. Clear limits on what AI can do, especially anything that acts in your systems.
  • Human oversight. Review and approval for high-stakes actions, so a person stays accountable.
  • Audit logging. A traceable record of what AI accessed and did.
  • Know where data goes. Get written terms — especially that your data isn’t used to train the vendor’s models.
  • Avoid lock-in. A model-agnostic approach keeps you in control of data and choices.

The risks these address

  • Data exposure — AI seeing or leaking data it shouldn’t.
  • Ungoverned actions — an agent acting beyond its scope.
  • Missing audit trails — no record to review or explain.
  • Vendor lock-in — depending on one provider whose data handling you don’t control.

The data-control foundation

The most important decision is where your data goes. An architecture that routes everything through one external provider concentrates both exposure and lock-in. One that keeps your data under your control — and lets you choose and change models — is the safer foundation, which is why dgm builds on a model-agnostic platform.

Design it in, not on

Retrofitting security after AI is already loose in your operation is far harder than designing it in. Access controls, boundaries, oversight, and audit should be part of the implementation, not an afterthought.

How dgm helps

dgm builds security in by design — least-privilege access, action boundaries, human oversight, and audit — on the model-agnostic osFoundry platform that keeps your data under your control, as part of the $3,999/month implementation (after a $399 assessment). See AI security & governance consulting. If you’d rather explore the platform yourself first, go straight to osFoundry; if you want AI secured properly, that’s where dgm comes in.