Shadow AI vs Shadow IT: Approved Apps Can Hide Unapproved Use

What is the difference between shadow AI and shadow IT?

Shadow IT includes software, devices and services used for work without the required approval or oversight. An employee might adopt an unapproved file-sharing service or install an unmanaged desktop app. Discovery, ownership, access review and procurement help bring that technology under control.

Shadow AI is AI use outside that oversight. It can involve an unknown app, but it can also happen inside software the company already approves. A personal AI account, an enabled assistant or an agent connected to company files can change the risk without adding a new vendor to the inventory.

The categories overlap. The difference is the scope of the review. An app approval alone does not establish which AI uses, accounts, data or actions the company has authorized.

Why can shadow AI hide inside approved apps?

A company can approve an AI service for its managed workspace while an employee uses a personal account on that same service. The app name and destination may look familiar. The account can have different administration, retention and sharing settings. Personal use is not automatically unsafe, but it may fall outside the company's agreement and policy.

AI features inside SaaS create a similar review problem. An approved writing tool, meeting platform or support system may offer an assistant that was never part of the original assessment. Review what it can access, where information goes and which settings govern its use.

Account-aware AI access and feature-level review make approval more precise. Define the approved workspace, permitted tasks and allowed data. Make those boundaries clear enough that employees can follow them.

How do extensions, agents and OAuth grants change the risk?

An AI extension can introduce another party into a browser workflow. Depending on its permissions, it may read content on pages the employee visits. Approving the underlying website does not mean the extension has been reviewed. Include extensions in the inventory and assess their access separately.

An agent can move beyond generating text to using tools and changing resources. A coding agent may work with local files, plugins or MCP servers. Review its owner, permitted tasks and authority to act, including which actions require human approval.

An OAuth grant can give an AI app continuing access to company resources, subject to its permissions and token lifecycle. Closing the app does not necessarily remove that access. OAuth app risk reviews should establish who granted access, what it permits and when to revoke it.

What does shadow AI look like in an enterprise?

Consider a hypothetical sales team with an approved AI workspace. An employee signs into a personal account on the same service and pastes a draft customer proposal. They also install a browser writing extension and authorize a meeting assistant to access their work calendar.

The app inventory may already list the AI service and meeting platform. That still leaves separate questions about the personal account, proposal content, extension permissions and calendar grant. Each needs an owner and a policy decision.

The response should preserve the approved workflow. Direct the employee to the company workspace, apply rules for customer data, review the extension and remove unnecessary app access. Explain the permitted route so the same task does not move to another unreviewed tool.

Which do you need: shadow IT controls or shadow AI controls?

Keep shadow IT controls as the foundation. You still need software inventory, vendor review, managed devices and access lifecycle management. Extend that foundation when employees use AI, including AI features within existing tools. Buying another discovery tool alone will not define acceptable use.

Choose controls against concrete workflows. Ask whether they distinguish approved accounts, protect sensitive submissions and address extensions or agent actions where your employees work. Validate supported apps, devices and response options during evaluation.

• Start with inventory and ownership if you cannot establish which apps and services employees use.
• Prioritize account and data controls when approved AI services are used through personal accounts.
• Add agent and permission governance when AI can access connected resources or perform actions.
• Document approved workflows in an AI acceptable use policy and assign responsibility for exceptions.

Where Identra fits

In the browser, Identra discovers AI apps and whether people use work or personal accounts with them, and can allow, redirect to the company AI workspace or block access by signed-in account for supported AI services. It also inventories installed browser extensions, flags risky ones, and can disable them by policy. On macOS and Windows, it discovers coding agents, desktop AI apps, MCP servers, skills and plugins, and records agent runs with the user and outcome. Across connected providers, analysts can review OAuth grants and revoke risky ones. Where the person is known, browser, endpoint and provider activity ties to one person and one timeline.

Frequently asked questions

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