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Shadow AI monitoring

Find the AI applications your workforce already uses.

Shadow AI is the use of AI applications, services, models or embedded features outside an organisation’s approved inventory and governance process.

Promptective brings recognised and suspected browser and desktop AI activity into one governance workflow, then shows which supported interactions are protected.

Direct answers

Clear answers for Security, IT and Compliance teams

What is Shadow AI?

Shadow AI is the use of an AI application, service, model or embedded feature outside an organisation’s approved inventory and governance process. It can include public tools, AI features inside broader applications, code assistants, agents and direct model connections.

How can an organisation detect Shadow AI?

Combine an owner-reviewed AI register with signals from managed browsers and desktop devices. Promptective surfaces recognised AI applications and suspected connections so Security, Compliance and IT teams can confirm the owner, purpose and required policy.

What is the difference between observed and protected AI activity?

Observed means Promptective detected evidence that an AI application or connection was used. Protected means Promptective checked a supported interaction before delivery, applied organisation policy and recorded the result.

Can Shadow AI be blocked without storing employee prompts?

Yes. Promptective can block supported AI traffic according to organisation policy while keeping prompt and response text out of routine records. Other discovered activity remains visible for review.

What evidence should a Shadow AI inventory contain?

Record the AI application or feature, provider, owner, purpose, approval state, device, first and last seen dates, protection status and review history. Promptective keeps prompt, response and tool-result text out of routine inventory evidence.

Shadow AI risks

Unknown use creates unknown control gaps.

Assess the exact tool, account, data, permissions and business purpose before assigning risk.

Sensitive information exposure

Prompts, files and tool inputs can contain personal information, credentials, source code or commercial material that the organisation did not intend to share.

Unreviewed supplier terms

Retention, model-training, access, residency and deletion settings may not match organisation policy until the provider and account configuration are reviewed.

Governance and response gaps

An unregistered use can lack an accountable owner, risk assessment, approved purpose, incident route, exception expiry or evidence for later review.

Uncontrolled actions

An AI feature, agent or connected tool with external permissions can read or change systems beyond its intended purpose. Risk depends on the exact identity, scope and action.

Observed versus protected

Know which AI activity is protected.

Promptective keeps newly discovered activity separate from supported interactions that were checked before delivery.

Discovered

Promptective found recognised AI activity or a suspected connection that needs review.

Reviewed

Your team confirmed the application, provider, owner, business purpose and approval state.

Protected

Promptective checked the supported interaction, applied organisation policy and recorded whether content was delivered.

Each protected interaction has a recorded decision. The receipt shows the application, policy, result and whether content was delivered.

Inventory evidence

What a defensible Shadow AI inventory should contain

Keep enough evidence to explain the classification, protection and review without storing prompt or response text in routine inventory records.

Asset and ownership

Canonical application or feature, provider, account or workspace, accountable owner, users, business purpose and approval state.

Observation provenance

The managed browser or device that produced the signal, its first and last seen dates and the review status.

Data and action context

Reviewed information classes, integrations, model or service origin, permissions and external actions.

Protection boundary

Whether activity was discovered or protected, tied to the application, provider, device and active Promptective integration.

Policy and outcome

Policy and detector versions, decision, reason identifiers, transformations, delivery or execution result, and control-health evidence.

Risk and review history

Risk reasons, treatment, exception and expiry, reviewer, incidents, last assessment and next review date, without routine prompt or response plaintext.

Promptective protection

One policy across the AI paths your team uses.

Promptective applies the same organisation policy and decision record across supported browser, desktop, provider, code-assistant and custom-agent workflows.

Browser

Typed, pasted, dropped and uploaded content

Promptective checks supported browser AI interactions before content reaches the provider.

Explore browser protection

Desktop

AI apps and code assistants

Promptective keeps most policy decisions on the device and protects supported desktop and command-line AI workflows.

Explore desktop protection

Custom agents

Tool and action controls

Apply organisation policy before supported agents send content or execute external actions, with a receipt for each decision.

Explore agent security

Source transparency

Australian guidance referenced

  1. 1.
    Guidance for AI adoption: implementation guidance

    Australian Government, National AI Centre

  2. 2.
    Guidance on privacy and the use of commercially available AI products

    Office of the Australian Information Commissioner

Governance walkthrough

See the AI activity your organisation can govern.

Tell us which browser, desktop and agent workflows your team uses. We will show how Promptective discovers activity, applies policy and records each decision.

Shadow AI Monitoring and Governance | Promptective