Traditional data loss prevention was built for files, email, and network traffic. The fastest-growing risk now lives in the browser: prompts typed into ChatGPT, Claude, Gemini, and AI features embedded in SaaS. That usage is invisible to legacy DLP. Here is the honest gap, and how to switch to Workforce AI Security without ripping anything out.
Legacy DLP cannot see the prompt. When AI runs in the browser, the prompt and response never appear as a file transfer or an email attachment, so network and endpoint DLP have nothing to inspect.
This is not a vendor flaw, it is a category limitation. DLP was designed before generative AI moved work into the browser. Blocking an entire AI domain stops the tool but also stops the productivity gain and pushes employees onto personal devices, where you have no visibility at all. Workforce AI Security closes the gap by operating at the browser and endpoint layer, where the prompt actually exists.
A fair, side-by-side look at where traditional DLP stops and where an AI-native layer is needed. Legacy DLP is described as a category, not any single vendor.
| Capability | Legacy DLP | Workforce AI Security (Aona) |
|---|---|---|
| Prompt visibility | ✕Cannot see prompt content typed into browser-based AI tools | ✓Sees the actual prompt at the browser and endpoint, where it exists |
| Native and browser AI apps | ✕Browser-based AI usage is invisible to network and endpoint DLP | ✓Discovers AI tools used in the browser and in desktop apps |
| Shadow AI discovery | ✕No inventory of unapproved AI tools or embedded AI features | ✓Full AI tool inventory, including unapproved and embedded AI |
| Real-time employee coaching | ✕Alerts security after the fact, or hard-blocks the whole domain | ✓Coaches the employee in the moment of a risky AI prompt |
| DLP for AI tools | ~Built for files, email, and network egress, not AI prompts | ✓Policy applied to AI tools specifically, at the prompt layer |
| Behaviour change over time | ✕Static rules; employees route around blocks to personal devices | ✓Coaching and upskilling shift how the workforce uses AI |
Legend: ✓ covered · ~ partial or blunt (domain-level only) · ✕ not addressed by the legacy DLP category.
Switching to Workforce AI Security is additive, not a rip-and-replace. You keep legacy DLP for what it is good at and add the AI layer on top, in phases.
Leave legacy DLP in place for email, managed file shares, and traditional endpoint egress. Nothing is ripped out. Aona is additive and runs alongside it.
Push the Aona browser plugin and the Windows and macOS desktop app through your existing MDM or group policy. No network proxy and no VPN to stand up.
See your real AI usage and a complete shadow AI inventory, including the browser-based and native AI apps that legacy DLP cannot see.
Enable real-time coaching at the moment of a risky prompt, then apply DLP policy to AI tools. Roll out by team so adoption stays smooth.
The two capabilities legacy DLP cannot deliver for AI: prompt-level DLP for AI tools, and discovery of the AI tools employees use in the first place.
Apply data loss prevention at the prompt layer, where legacy DLP cannot reach. See and govern sensitive data before it enters a browser-based AI tool, without blocking the whole domain.
See DLP for ChatGPT →Discover every AI tool your workforce uses, including the browser-based and embedded AI that is invisible to network and endpoint DLP. You cannot govern what you cannot see.
See shadow AI detection →Book a demo to see prompt-level visibility, shadow AI discovery, and real-time coaching on your own environment. Or start a 30-day free trial, no credit card required.