What Is DLP for AI?
Conventional DLP tools are built to inspect structured data movement like file transfers and email attachments, and generally don't parse conversational input, model responses, or the free-form traffic between an AI agent and its connected tools. As organizations route more sensitive data through AI applications, DLP for AI has become a necessary complement to, not a replacement for, existing DLP programs.
Why It Matters
- Sensitive data can now leave an organization through a chat interface, not just a file transfer, a path most legacy DLP tools simply don't monitor.
- Agent-to-tool traffic is a newer, less visible data path than either of those, and it's growing as agentic adoption grows.
- This is additive to existing security stacks, not a rip-and-replace, organizations still need traditional DLP for traditional data movement.
