If We Give Users an AI Chat Interface, What Stops Them Asking Away Our Trade Secrets?

During a recent demo of Interakt, an AI powered chat interface, someone asked me a question that stopped me mid sentence.

"If we connect this to our data and give users a chat window, what is stopping them from asking away every trade secret we have?"

My first instinct was to reassure them. But then I thought about it for a second. They were not wrong to ask.

There is a version of this that is built badly. Where AI connects broadly to your data with very little in between, and yes, a curious or malicious user could piece together things they were never supposed to see. The concern is valid. If someone builds an AI chat interface and connects it directly to a database without proper access controls, without scoping what data the AI can reach, without filtering what it can surface, then the fear is entirely justified.

But there is also a version that is built right.

Most companies have spent years building business logic into their API layer. Authentication, permissions, rules about who sees what. A well built AI interface respects all of that. It does not connect to your database directly and hand users a skeleton key. It calls your APIs the same way every other part of your system does, which means it operates within the same boundaries you have already defined.

The same applies to what the AI actually knows. Rather than giving it access to everything and hoping it behaves, good implementations scope the knowledge deliberately. You define what the AI can draw from. It cannot answer questions about things outside that scope because as far as it is concerned they do not exist.

A topic that has been generating a lot of conversation lately is MCP servers, the Model Context Protocol that allows AI to connect to tools and data sources dynamically. The concern is understandable. MCP is powerful precisely because it removes friction, you can connect AI to almost anything quickly. That power is also the risk. A misconfigured MCP setup with broad permissions could let an AI traverse far more of your system than intended. The answer is the same principle that applies everywhere else. Least privilege. The AI gets access to exactly what it needs to do its job and nothing more.

The question asked in that demo was one of the smartest things I heard all week. Not because the risk is unavoidable, but because it is exactly the right question to ask before you start building.

The security architecture conversation should happen before the first line of code is written, not after. What data can this AI access? Through what layer? Who is it serving and what should they be able to see? Get those answers in place first. The build is the straightforward part.