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AI DLP

AI DLP foryour workforce

Protect sensitive prompts and files before they reach a supported AI service. Use this guide to choose the app, input path and policy response to evaluate with Aona.

SAISIE PROTÉGÉEChamps sensibles remplacés

[CLIENT] et [COMPTE] sont protégés dans cet exemple synthétique.

Exemple synthétique. Validez le client et le chemin de politique concernés.

AI-native
Sensitive-data detection
Real-time
Enforcement before AI submission
10,000+
AI tools in the catalogue
SOC 2
Type 2 report available
Plan your evaluation

Three questions before choosing AI DLP

Start with one employee action and a result your security team can verify.

01

Which app and action?

Name the AI service, account type, browser or desktop client, and whether the employee types, pastes or uploads a file. A supported provider name alone does not establish coverage for every action.

02

What should happen before submission?

Choose a sensitive-data category and an expected response. Aona can block or redact supported inputs according to policy. Test the response with synthetic data, including an allowed input, before a rollout.

03

What does your current stack cover?

Existing DLP may already inspect AI submissions through endpoint, browser or network controls. Compare the same input, device, licensing and policy conditions to identify what an Aona evaluation should add.

Evidence and further reading

92.8%
Shadow AI prompts fell from 446 to 32 in 30 days, a 92.8% reduction after guardrails were enabled.
One Australian healthcare organisation, after platform blocking and pre-submission guardrails. This is a single deployment outcome. Read the case study

FAQ

AI DLP questions

What is AI DLP?
AI DLP (AI data loss prevention) is DLP built for the way employees actually use AI: typing prompts and uploading files into tools like ChatGPT, Microsoft Copilot, Gemini, and Claude. Aona inspects supported prompts and attachments through a deployed browser plugin or native app, and blocks or redacts sensitive data such as PII, financial records and source code before submission. Coverage depends on the supported client and input path.
How is AI DLP different from legacy DLP?
AI DLP focuses on the prompts and files employees submit to AI services. Existing DLP can also protect some AI interactions through endpoint, browser or network inspection, depending on configuration and licensing. Compare the exact app, account, client and input path. Aona adds policy-driven blocking or redaction on supported interactions through its deployed browser plugin or native app.
Which AI tools does AI DLP need to cover?
Shadow AI extends beyond familiar services such as ChatGPT, Microsoft Copilot, Gemini and Claude to niche tools that may never have gone through procurement. Aona’s catalogue contains 10,000+ AI tools for discovery and risk context. Active blocking and redaction depend on the supported tool, client and input path, rather than applying uniformly to every catalogue entry.
Does AI DLP mean blocking employees from using AI?
No. The configured policy determines which supported submissions are blocked or redacted and what guidance the employee receives. Redaction can preserve a useful request while replacing sensitive entities. Validate the intended outcome and an allowed input with synthetic data; no single policy response fits every app or data category.
Do we need to replace our existing DLP to add AI DLP?
Adding Aona does not require replacing every established DLP control. First map what your current stack covers, then evaluate the employee AI actions that need additional protection. Check the intended device, client, policy response and coexistence with your installed controls during the evaluation.
Get started

See AI DLP running on your own AI usage

Start a 30-day free trial to evaluate your DLP policy, or book a demo to see prompt inspection, redaction and hard blocks working together.

30-day free trial · SOC 2 Type 2 report
AI DLP: Data Loss Prevention for AI Tools | Aona AI