Prevent data leakage when employees use AI: A practical operating guide

Quick answer

Define approved AI tools, permitted inputs, decision owners and incident reporting. Test real transfer paths with synthetic data rather than assuming one control covers every route.

An employee may upload a contract or customer file to AI with good intentions. Risk arises when the destination or data use has not been approved. Prevention needs usable alternatives, understandable rules, and tested technical controls.

Define permitted information

Ask data owners to classify information by impact, using levels such as Public, Internal, Confidential, and Restricted. Specify which AI services may process each level, approval requirements, and necessary minimization. Use synthetic context for ordinary drafting instead of attaching an entire real document.

Test distinct transfer paths

File uploads, pasted text, images, browser extensions, and API connections are different paths. Endpoint Central describes endpoint DLP controls, but this does not establish identical coverage for every AI service. Build a test matrix for actual browsers, operating systems, and versions.

Make accidental disclosure reportable

Stop further submission, record the time, service, account, and data category, and notify the responsible team through an approved channel. Do not attach the confidential file again as evidence. Assess access, retention, and revocation using provider-specific facts; deleting visible conversation text does not prove deletion everywhere.

Implementation checklist

• Maintain an approved AI list with accountable owners.
• Give departments concrete permitted and prohibited examples.
• Test files, text, images, and integrations using synthetic data.
• Assign reporting contacts, evidence handling, and policy review dates.

Start with one necessary AI workflow in a department with clearly understood risk. KTNBS can help define a synthetic-data evaluation of the relevant DLP paths.

A scenario to take into your evaluation

Test typed text, pasted text, attachments and screenshots independently using synthetic data.

This is a proposed test, not a measured result or customer endorsement. Record the actual platform and edition, owner, expected result and observed outcome before expanding scope.