Large language models unlock real productivity, but they also introduce a new and unfamiliar attack surface. Treating an AI feature like any other untrusted input is the first step toward using it safely.
Start with governance: define acceptable use, document which data may be sent to a model, and record who owns the risk. Clear policy prevents well-meaning teams from quietly sending sensitive records to third-party services.
On the technical side, assume prompt injection will happen. Validate and constrain model inputs and outputs, keep the model away from privileged actions it does not need, and log interactions so you can investigate later.
Finally, watch for data leakage. Mask sensitive fields, prefer retrieval patterns that keep secrets out of prompts, and review vendor retention terms. Responsible AI adoption is mostly disciplined engineering.
