SHADOW AI DETECTION & DISCOVERY
Shadow AI detection. Know what your team is using.
See the AI tools in use, the teams behind them and where to look next. Turn employee AI activity into a clearer security decision.
Start with deployed endpoints and an agreed observation scope.
Sample workspaceAI platform usage
BEYOND THE APPROVED LIST
You approved one AI tool.
Your people found more.
Shadow AI is AI used at work outside your organisation’s approval or visibility. Discovery turns that blind spot into a starting point for action.
Microsoft CopilotOn your listChatGPTTo reviewClaudeTo reviewGeminiTo reviewWHERE VISIBILITY STARTS
At the endpoint.
With the employee’s workflow.
Aona uses its browser plugin and native endpoint app to observe supported AI activity. An installed, configured client enables visibility, not a catalogue entry.
AI in the browser
Observe supported AI activity through the Aona plugin in Chrome, Edge, Firefox and Safari.
Check your coverage
DISCOVERY VIEWReview the tools in use
An installed, configured browser plugin is required.Discovery does not mean every website supports prompt enforcement.
Deployment and privacy details
Devices without a deployed Aona client are outside the observed scope. Aona discovery is not an agentless network scan, an identity-log scan or a scan of every SaaS integration. Check the managed endpoints, browser versions, collection settings and employee communication needed for your rollout.
Backend hosting and prompt processing are separate choices. The backend can run in your cloud, on-premises or on Aona-managed servers. Prompt processing can run on the user device, in your environment or on Aona-managed servers. Confirm the supported feature combination and review third-party AI-provider processing separately.
Plan your deploymentA BASELINE YOU CAN USE
From a tool inventory
to your next decision.
Leave with a clear next step.
Give the review an owner. Approve a workflow, investigate a gap or evaluate a supported control.
Discovery vs enforcementA review agenda, not an automated compliance verdict.
What should a Shadow AI detection tool prove?
Keep a short evidence record for the population and activity you can actually observe.
- Covered population
- Record the employee groups and endpoints in scope, which have the client installed, and the observation dates. Separate covered users from active AI users.
- A known activity
- Use a synthetic prompt on an agreed app and client. Check that the observed tool and time match the test; repeat for each input path that matters.
- Gaps and next controls
- No activity is not proof of no AI use. List missing clients and unobserved paths. Evaluate blocking or redaction separately from discovery.
- Privacy and review
- Agree employee notice, fields collected, retention and report access. Name the person who will review an unapproved tool and the evidence they need.
DISCOVER. THEN CHOOSE.
Visibility opens the right conversation.
A CLOSER LOOK
Shadow AI discovery,
without the guesswork.
The practical questions security and IT teams ask before starting.
What is shadow AI detection and discovery?
Shadow AI detection identifies AI activity that sits outside an organisation’s approved tools or known inventory. Discovery builds an inventory of the observed tools and usage so security and IT can review ownership, business purpose and next actions. Aona’s visibility depends on the deployed browser or native endpoint client and the activity it supports, not on an agentless scan of every device or SaaS account.
How does Aona discover employee AI usage?
Aona observes supported activity through its Chrome, Edge, Firefox or Safari browser plugin and Windows or macOS native endpoint app. The admin view brings tool and usage information together for review. Agree on the managed devices, employee groups, observation period and collection settings before interpreting the inventory. Unmanaged devices without Aona are outside that scope.
What does 10,000+ AI tools tracked mean?
It describes Aona’s AI tool catalogue, not the number of tools a customer actively uses or the number that support identical controls. Observed usage depends on the installed client and supported activity path. Prompt blocking and redaction must be evaluated separately for the app, action and deployment you need.
How long does it take to establish a Shadow AI baseline?
Timing depends on deployment coverage, collection settings and employee activity. Agree on an observation period, then use the initial baseline to identify gaps and decide whether to extend it. A baseline is not a guarantee that every employee, occasional use or AI tool appears within a fixed number of hours.
Is discovering an AI tool the same as blocking sensitive data?
No. Discovery answers which AI tools and activity are visible. Enforcement applies an evaluated policy response, such as redaction or blocking, on a supported interaction. Use the discovery baseline to prioritise workflows, then validate the relevant app, input path and policy before rolling out data protection.
Can Aona discover employee-run AI agents?
AI agent inspection is available through the native endpoint app in a limited rollout. It extends visibility to supported local agents and associated context. Confirm the available release, runtime, device and privacy scope with Aona; do not assume universal agent discovery or agent-action enforcement.
See what your first discovery review could look like.
Bring your approved tool list, managed endpoint mix and visibility questions. We’ll walk through the discovery scope, the inventory view and the controls to evaluate next.