AI can leak private data if sensitive information is sent to the wrong service, stored in logs, exposed through tool results, included in prompts, or returned to the wrong user.
In practice
The risk increases when AI tools connect to email, files, databases, CRMs, support systems, or internal documents. Permissions and user identity need to follow the data.
What to watch
Private data protection is a system design problem. Use least privilege, access checks, redaction, audit logs, retention controls, and human review for sensitive workflows.