The AI privacy checklist before uploading company data
Before teams upload documents, code or customer data to an AI tool, they should check retention, training use, permissions and auditability.

Convenience is not a data policy
AI tools make it easy to paste documents, transcripts, code and customer messages into a chat box. That convenience can create risk when teams do not know how data is stored, whether it may be used for training or who can access the workspace.
The minimum checklist
| Area | Question |
|---|---|
| Retention | How long does the provider store inputs and outputs? |
| Training | Can user data be used to improve models? |
| Access | Who can view shared chats, files or projects? |
| Audit | Can admins review usage and revoke access? |
Why this matters
AI adoption often starts with individual productivity and later becomes company infrastructure. The earlier a team checks privacy and security boundaries, the easier it is to avoid messy cleanup after sensitive data has already moved.
Author
Maya Turner
Colaborador editorial.
