Can chatbots leak your data: Keeping AI systems safe

A project deadline is approaching. A manager opens a chatbot to speed things up. He asks it to summarise a client brief, shares internal timelines and even types in pricing details to get a faster draft. The conversation flows smoothly, the work gets done, and the chat is closed.

- NEEHAR PATHARE

project deadline is approaching. A manager opens a chatbot to speed things up. He asks it to summarise a client brief, shares internal timelines and even types in pricing details to get a faster draft. The conversation flows smoothly, the work gets done, and the chat is closed.

But the data doesn't disappear.

Chatbots powered by generative AI are designed to learn from interactions. The more users share, the more these systems improve—but also, the more they retain. What feels like a private exchange can quietly turn into a digital footprint, stored, processed, and potentially exposed.

Chatbots that remember more than they should Unlike conventional digital tools, generative AI chatbots are built on large language models that rely on enormous volumes of data to function. These systems not only interpret language and identify context but also generate nuanced responses. By doing so, they often process highly specific, sometimes confidential, as well as sensitive inputs. From internal reports and business strategies to personal details and client records, these inputs cover all. Every interaction contributes to the model's refinement, but it also expands the digital memory these systems carry forward.

The concern lies in what happens to that memory. When sensitive data is retained—whether temporarily or for model training—it creates opportunities for leakage. The more these systems are integrated into everyday workflows, the more likely it becomes that critical information is unintentionally exposed or stored in ways users are not completely aware of.