To stop employees using unapproved AI apps, give them a clear way to disclose the tools they use, request approval for new ones, and get a suitable alternative for common tasks. A rule that simply says “don’t use AI” may leave people guessing, while an open-ended policy can put company information at risk.
The goal is to make AI use visible and manageable. Start by finding out what is already in use, decide which tools and uses are acceptable, and give employees guidance they can apply in everyday work. That approach helps address shadow AI without making useful work harder than it needs to be.
Start by finding out what employees already use
Begin with a straightforward, no-blame conversation. Ask employees which AI apps or features they use, what work they use them for, and whether they access them through a work account, personal account, browser extension, or another tool. Explain that the purpose is to understand the current picture and set clear safeguards, not to punish people for raising a concern.
Look beyond standalone chatbots. AI may be built into software employees already use, added through a browser extension, or included in a coding or writing tool. Ask teams to mention features that are switched on inside existing applications, not just apps they deliberately signed up for.
Make a simple inventory with the tool name, business purpose, users or teams, account type, and kinds of information involved. Note whether the app is being tested, used regularly, or no longer needed. Guidance from Microsoft on discovering AI apps also emphasizes identifying AI use and the data connected to it.
Keep the discovery process easy to complete. A short staff questionnaire, manager check-ins, and a review of software and browser extensions can help a smaller business build an initial list without starting with specialized security tools.
Set a clear boundary around company information
Employees need plain-language examples of what they should not submit to an AI app unless the specific tool and use have been approved. Consider calling out:
- Customer, patient, or client records and identifying details.
- Employee information, including private personnel or payroll details.
- Financial records, credentials, access tokens, and confidential account information.
- Contracts, proposals, internal documents, or business plans that are not public.
- Operational details that could expose how systems, facilities, or processes are managed.
Also explain that removing a name may not be enough to make information safe to share. Context, combinations of details, or attachments can still reveal who or what the information concerns. When employees are unsure, the default should be to pause and ask rather than paste the material into an unapproved tool.
For a deeper review of how information is protected across business systems, see Zevonix’s guidance on data protection for businesses.
Create a lightweight AI app approval process
A workable approval process does not need to be complicated. Give employees one place to request a review, name someone responsible for making or coordinating the decision, and tell staff what information to provide. A basic request can ask:
- What task or problem would the app help with?
- Who would use it, and through what type of account?
- What information would employees enter, upload, or connect?
- Does the app connect to email, files, customer systems, or other business tools?
- What does the provider say about handling submitted information, account access, and data retention?
- Is there an approved tool or existing process that could meet the same need?
Review each request according to the information involved and the access the app would receive. A tool used to summarize public material presents a different review question from an assistant connected to internal files or customer records. Consider the business purpose, the sensitivity of the data, who can access the tool, and what could happen if information were exposed or used unexpectedly.
Then make the outcome clear: approve the tool for a defined use, ask for more information, restrict certain features or data, or decline the request. Record the decision and any conditions so employees and managers can refer to the same guidance. The NIST AI RMF Playbook’s Govern guidance can help organizations think through responsibilities and oversight as they set up their approach.
For a new or changing use, set a review point rather than treating approval as permanent. A change in the app’s features, connected data, account setup, or intended task may warrant another look.
Write an AI acceptable use policy employees can follow
An AI acceptable use policy should answer practical questions, not just state broad principles. Keep it easy to find and cover:
- Which AI tools are approved, and what work they may be used for.
- What kinds of company information may not be entered into unapproved tools.
- How to request review of a new app or use case.
- What employees should check before relying on AI-generated work.
- How to report accidental sharing or ask for help.
- Who owns the policy and how staff will hear about changes.
Pair the policy with short employee AI training. Use examples drawn from real workflows, such as drafting a public-facing summary versus processing a customer record. Make it clear that employees remain responsible for checking work before they share or act on it. Reinforce the guidance when teams adopt a new tool or when approved uses change.
Policies are more useful when the approved path is practical. Ask employees which repetitive or time-consuming tasks they want help with, then look for tools that match those needs and have been reviewed for the intended use. If staff have to choose between an unavailable approved tool and an easy unapproved one, the process is not serving them well.
Choose sensible controls and make reporting easy
Based on your inventory and risk review, decide whether each app should be approved, restricted, or blocked. Blocking can make sense when a tool presents unacceptable risk or has no suitable business use. But a blanket block on every unapproved app may not address the underlying need. Pair restrictions with an approval route and useful alternatives.
Make the rules visible in the places employees work. Depending on your setup, that could mean sharing an approved-tools list, reviewing access to browser extensions, or using available account and network settings to limit access to particular apps. Be transparent about any monitoring and keep it focused on business risk and company systems. If you are unsure what controls are available in your environment, an IT review can help clarify practical options.
Tell employees exactly what to do if they accidentally share sensitive information. The first step should be to stop using the tool for that information and report what happened promptly through a named manager, IT contact, or security channel. Ask them to share the app name, the type of information involved, and when it happened, without forwarding or exposing the sensitive material again. Respond calmly and focus first on understanding and containing the issue.
Clear reporting helps the business assess what happened and decide on appropriate next steps. It also gives you a chance to improve the policy, training, or controls where staff are uncertain. For related safeguards around business systems, see Zevonix’s overview of network security services.
Frequently asked questions
How can a small business monitor AI app use without enterprise security software?
Start with a staff survey, manager conversations, and a review of apps, accounts, and browser extensions already in use. Maintain a shared inventory and a simple process for reporting new tools. These steps can create visibility before you decide whether additional technical controls are needed.
Should a company block all unapproved AI tools?
Not necessarily. Restrict or block tools when the risk calls for it, but also give employees a clear way to request approval and access a suitable alternative. Otherwise, staff may continue using tools outside the process.
How should employees report accidentally sharing sensitive information?
Provide a named contact or reporting channel and ask employees to report promptly. They should identify the app, the general type of information, and when the incident occurred, without sharing the sensitive content again. Keep the response focused on understanding and containing the issue.
How can a business offer approved AI tools employees will actually use?
Ask staff about the tasks they want to improve, then review tools against those needs and the information they would handle. Explain what the approved tool is for, how to access it, and where to ask questions.
Make safe AI use the easy path
Stopping unapproved AI use is an ongoing process: understand what employees are using, set clear data boundaries, review requests consistently, and make it easy to ask for help. If your business wants support reviewing its technology safeguards and approval process, contact Zevonix to request a free IT assessment.