What data most often leaks into AI tools?

In practice: customer and employee personal data, internal documents, source code with embedded secrets, and financial or deal information. The mix depends on the industry and on which teams use AI most.

AI governance glossary

What is AI data loss prevention (AI DLP)?

Definition

AI data loss prevention (AI DLP) is a set of controls that inspect the content people and applications send to AI tools (prompts, pasted text and uploaded files) and stop sensitive data from leaving the organization, by warning the user, redacting the sensitive parts, blocking the request, or routing it to an approved model.

Why traditional DLP falls short

Traditional DLP was built for email, file shares and USB drives. AI interactions are conversational, often encrypted inside web apps, and spread across many tools and APIs. AI DLP understands AI sessions, account types and model APIs.

Common detectors

Personal data, health data, payment card numbers, national identifiers, credentials and API keys, source code, and organization-specific terms such as project code names, often combined with exact data matching against real records.

Redaction beats blocking

Blocking stops work and pushes people to workarounds. Redaction replaces sensitive spans with placeholders so the AI can still help, and can restore the originals in the response.