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A workable shadow AI policy gives employees a clear list of approved tools and tasks, sets boundaries for business data, requires human review, and provides a quick way to request approval for something new. A blanket ban can leave workers guessing; unrestricted use can expose business data and work product to risks associated with third-party generative AI.
Here, “shadow AI” means employee use of AI services or features the business has not reviewed, approved, or put under workplace rules. It is a practical working definition, not a formal term defined in NIST guidance. The framework below adapts NIST recommendations; it is not a mandated NIST template.
What should a small-business shadow AI policy cover?
Keep the policy short enough to use and specific enough to guide decisions. It should tell employees what they can use, what information they can enter, how to check outputs, how to seek approval, and what to do if something goes wrong. NIST’s Generative AI Profile recommends updating acceptable-use policies and identifies data protection, retention, education, monitoring, and incident response as governance practices. NIST AI 600-1 was published July 26, 2024.
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NIST also identifies intellectual-property, privacy, and information-security risks associated with third-party generative AI. Its guidance informs the policy choices below, but it does not prescribe one universal list of prohibited data or one monitoring method for every employer. NIST AI 600-1
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Set boundaries around tools and tasks
List approved services and the work each may support. Approval for drafting internal announcements, for example, does not automatically mean a service is approved to process customer records or connect to a company drive. Name the person responsible for approving additions and reviewing existing approvals.
Protect business and third-party information
Tell employees not to enter sensitive or protected information into an unreviewed service. Adapt examples to the business’s data and agreements: these might include customer or employee personal data, credentials, confidential plans, source code, or material received under a client contract. Allow only the data needed for an approved task, and do not treat this list as a substitute for the company’s legal or contractual obligations.
Keep a person accountable for the output
Require a responsible employee to check AI-generated material before relying on it, sending it to a customer, publishing it, or using it in a consequential decision. The depth of review should reflect the task and its risks. Require disclosure of AI assistance when the business, a client, a contract, or applicable law calls for it.
Make approval and reporting usable
Give staff one clear route to request a tool or use case and one clear route to report accidental disclosure, unsafe output, or an unapproved integration. A policy that only says “don’t use AI” offers little help to someone who needs a permitted alternative or discovers a problem.
What to allow, ban, and monitor
Use this framework to write rules suited to your own systems, data, workforce, and contracts. Monitoring should be limited to what the business needs for security, policy compliance, and incident response, with appropriate notice and access controls.
| Policy area | Allow or require | Restrict or prohibit | Monitor or review |
|---|---|---|---|
| Tools | Services reviewed and approved for specified work tasks | Unreviewed services for protected business information | The approved-tool list, accountable owner, provider terms, and material feature changes |
| Data | Only the minimum, low-sensitivity information permitted for an approved task | Credentials, sensitive customer or employee information, confidential plans, or protected third-party content in unreviewed services | Exceptions, reported disclosures, and changes in provider data practices |
| Output | Approved assistance such as drafting, brainstorming, or summarizing, subject to employee review | Presenting unchecked generated material as verified fact, or using it unlawfully or harmfully | Quality checks proportionate to the use, incidents, and recurring failure patterns |
| Integrations | Reviewed extensions, plugins, APIs, and embedded AI features | Connecting business systems or granting data access without approval | Access scope, changes, and whether access remains necessary |
| Staff conduct | Training, a clear approval path, and incident reporting | Sharing accounts or bypassing company controls | Training completion and policy exceptions, with appropriate notice and access limits |
This is a practical application of NIST’s risk categories, not a universal NIST checklist. NIST advises due diligence for third-party generative AI, including attention to intellectual property, privacy, security, and ongoing monitoring. NIST AI 600-1
Copy-and-customize policy template
Replace the bracketed instructions with company-specific details before issuing this policy. Do not publish it as a universal or legally complete form.
1. Purpose and scope
This policy covers business use of AI tools and AI-enabled features by [employees, contractors, and other covered workers] on [company-managed and other covered devices or accounts]. It applies when AI is used to perform work, regardless of who owns the device or account. It does not prohibit personal AI use unrelated to company work, subject to other applicable workplace rules.
2. Approved tools and uses
Employees may use only tools listed in [location of approved-tool list] and only for the tasks stated there. The list identifies the tool, permitted tasks and users, data restrictions, business owner, approval date, and next review date. Contact [role or person] to request a new tool or use case. Do not assume that approval for one task or feature covers another.
3. Data and prohibited uses
Do not enter sensitive business, customer, employee, or third-party information into a service that has not been reviewed and approved for that data and task. Examples relevant to this company include [tailored examples]. Do not upload protected third-party material without authorization, bypass access controls, share accounts, or connect a service to company systems without approval.
Do not present unchecked AI output as verified fact. A human employee remains accountable for work produced with AI and for decisions made using it. Disclose AI assistance when required by [company, client, contract, or applicable legal obligation].
4. Required safeguards
- Use a company-managed account where one is available and approved.
- Provide only the information needed for the approved task.
- Check important claims, calculations, citations, and other material output before using it.
- Apply the review level required for the task and its consequences.
5. Approval process
Send requests to [contact or form]. Include the proposed tool and work task, the data it would receive, any requested integrations or access, and the business need. The reviewer will consider provider collection and retention practices, access and security controls, relevant terms, integration scope, and a fallback if the service is unavailable or unsuitable. Record the decision, any conditions, and when approval should be reviewed. NIST recommends updating third-party acquisition and procurement due diligence to address intellectual-property, privacy, security, and ongoing-monitoring concerns. NIST AI 600-1
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6. Monitoring and incident response
The company may review [specify business systems, accounts, or records] for [specific security and policy purposes]. Access to records is limited to [authorized roles] and handled under applicable company procedures and law. Employees should report accidental data submission, suspicious or unsafe output, or a newly discovered AI integration to [contact or reporting route] as soon as practicable. Do not conceal a mistake; prompt reporting helps the business respond.
7. Training and review
Employees must complete [training or briefing] and direct questions to [contact]. The policy owner is [role or person]. Review the policy and approved-tool list when a provider changes its terms or material features, a new use case is proposed, an incident occurs, or applicable obligations change; record the next review date for each approved tool.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to put the policy into practice
- Inventory current use. Ask teams which AI tools and AI-enabled features they already use for work, what tasks they support, what information they receive, and which systems they connect to. Use existing purchasing and security processes where practical.
- Approve a small starting set. Choose tools and tasks the business can review and support. Keep the initial approved list short and state its data restrictions clearly.
- Name an owner and a request route. Make one person or role accountable for decisions, recording conditions, and answering employee questions. A simple form or shared contact can be enough if requests receive a timely response.
- Explain the rules with job-specific examples. Show employees what data is sensitive in their work, how to check output, when disclosure is required, and how to report an incident.
- Revisit decisions when circumstances change. Reassess an approval after a provider changes terms or features, a new integration or use case is proposed, an incident occurs, or relevant obligations change.
NIST’s CSF 2.0 resources include materials tailored for small businesses, including organizations with modest or no cybersecurity plans. Its AI Risk Management Framework is voluntary guidance, not a certification requirement. The CSF 2.0 Quick-Start Guides page was updated August 25, 2026. NIST CSF 2.0 Quick-Start Guides
Monitoring, legal fit, and the limits of a template
Monitoring should answer a defined business need rather than become a blanket promise to inspect everything. State what systems or records may be reviewed, why, who may access them, and how exceptions and incidents are handled. Check employment, privacy, and other applicable laws before implementing monitoring. Requirements depend on jurisdiction, industry, workforce, contracts, and the data involved; the NIST materials cited here do not determine which rules apply to an individual business.
NIST’s AI Risk Management Framework page says version 1.0 is being revised, so consult the official page for updates when using it as guidance. The framework is voluntary. NIST AI Risk Management Framework
For organizations that need more technical implementation detail, NIST’s Control Overlays for Securing AI Systems project describes work on controls for different AI types and components, including generative AI assistants and agent systems. The project page describes implementation-focused guidance; it is not a ready-made small-business policy. NIST Control Overlays for Securing AI Systems
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