What traditional DLP does well
Traditional DLP has protected organisations for years by watching well-understood channels: outbound email, removable media, printing, and file transfers. It inspects those channels against policy and blocks or quarantines violations. For those use cases it remains essential.
Where it falls short on AI
The gap is not that legacy DLP is bad — it is that AI prompts do not look like the channels it watches. A prompt to ChatGPT is an ordinary HTTPS request to a trusted domain. It carries no attachment header, no email recipient, no file-transfer signature. So:
- Network and email DLP never see the prompt content at all.
- Personal AI accounts bypass corporate SSO and monitoring entirely.
- Desktop apps and IDE assistants sidestep browser-only controls.
- Blocking whole domains just moves usage to unmonitored devices.
Side by side
| Traditional DLP | AI DLP | |
|---|---|---|
| Channel watched | Email, USB, file uploads, network egress | AI prompts, pastes and file uploads to AI services |
| Visibility of AI use | Blind — prompts look like ordinary HTTPS to trusted domains | Purpose-built to see and classify AI interactions |
| Deployment | Network gateways, email proxies, agents | Endpoint inspection at the OS level — browser, desktop apps and IDEs |
| Coverage of personal accounts | None if it bypasses SSO / corporate network | Covered — detection is on the device, not the account |
| Where content is inspected | Often uploaded to a cloud service to be scanned | Locally on the endpoint — content never leaves the device |
Do you need both?
Usually, yes. AI DLP does not replace traditional DLP — it covers a channel traditional DLP was never designed for. Most organisations keep their email and network DLP for classic exfiltration and add AI-native, endpoint DLP to close the generative-AI gap. Together they cover the full picture.
AI-native and endpoint-based
Redbax is AI DLP built for the prompt: it inspects content at the OS level on Windows and macOS, classifies PII, PCI, credentials and source code locally, and applies block / warn / log policy before anything reaches an AI service. Start with the AI DLP guide or see the features.