AI Vocabulary · 07 When It Goes Wrong
What is Data Leakage?
Confidential information ending up where it shouldn't: in a prompt, a log, or another user's answer.
Data leakage with AI often starts innocently: an employee pastes a client contract, salary list or unreleased financial figures into a public chat tool. Depending on the tool and its settings, that data may be stored, reviewed by the provider or used for training.
Other routes include AI tools connected to too many internal systems, shared chats and links, memory features, and prompt injection attacks that trick an agent into sending data out.
Why it matters for you
Most leaks are not hacks, they are habits. If your team uses AI without clear rules, confidential data is probably already in tools you don't control.
Own it
Give your team approved tools with business terms, a simple rule for what may be entered where, and a safe option for sensitive work, such as an EU-hosted service or local AI. Banning AI rarely works; providing a good alternative does.
Where it comes from
Data leakage is an established security idea: sensitive information escaping its intended boundary. Generative AI gave it a new everyday route. A widely reported case: in 2023 Samsung restricted staff use of generative AI tools after engineers pasted internal source code into ChatGPT (Bloomberg). Many company AI policies were written in the months after.
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