Do these 3 things before closing this tab:
1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsBefore sending company information to an AI model, identify and minimize the data, confirm that the exact service and account are approved for that information and purpose, read the provider’s current data-use and retention terms, and verify security and incident commitments. If authorization or terms are unclear, do not submit the material; ask your privacy, security, legal, or records-management owner.
Why a quick check matters
An AI prompt can contain far more than the sentence you intended to ask about. An attached spreadsheet may include names, account numbers, hidden worksheets, comments, formulas, metadata, or credentials. A pasted contract may include customer restrictions or trade secrets. Once submitted, the information may be retained, reviewed, disclosed to service providers, transferred across locations, or used in model improvement depending on the product, account, settings, and contract.
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There is no universal “AI-safe” label. A consumer application, a business subscription, an application programming interface, and an enterprise deployment can have different controls and data terms. Approval for one product does not automatically approve another product from the same provider.
The Federal Trade Commission (FTC) says AI providers must honor privacy and confidentiality commitments, including promises about model training and other data use. Its business-security guidance also recommends taking stock of information, limiting access, retaining only what is needed, securely disposing of unneeded data, setting written security expectations for service providers, and verifying compliance.
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The Centers for Medicare & Medicaid Services (CMS) gives its workforce a deliberately simple warning: “If you hesitate to share information with an external expert, do not submit it to generative AI platforms.” That is agency guidance, not a rule for every private company, but it is a useful pause point.
Use the following process as a screening method, not as a substitute for the law, your contracts, or your organization’s policy.
What information is actually going into the model?
List the visible and hidden inputs
Write down the prompt, each attachment, pasted context, connected data source, and any automatic conversation history the tool may include. Check spreadsheets for hidden columns and sheets, documents for tracked changes and comments, images for readable screens or badges, and code for embedded keys or connection strings.
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Mark every relevant category before deciding whether to submit:
- Personal information, including names, contact details, identifiers, health information, financial details, or precise location.
- Customer or employee information.
- Credentials, API keys, tokens, private certificates, or other secrets.
- Trade secrets, source code, product roadmaps, pricing, security designs, or confidential plans.
- Regulated information subject to sector-specific requirements.
- Information received under a nondisclosure agreement, customer contract, employment agreement, or other restrictive term.
- Material whose disclosure could create a legal, safety, security, or competitive problem.
Do not treat a low-risk sentence as making a high-risk attachment safe. The strictest category in the complete submission should drive the decision.
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Can the task be completed with less data?
Remove unnecessary details
Keep only the fields the model needs to perform the task. A request to explain a database error may need the error text and a redacted schema, not customer rows. A request to rewrite a policy may need a short excerpt, not the entire internal manual.
Redact or substitute
Replace names, account numbers, email addresses, exact dates, locations, and unique identifiers with consistent placeholders such as Customer_A or synthetic examples. Remove secrets entirely rather than masking only part of a key. Generalize values where precision is not needed, and check that the redaction cannot be reversed from surrounding context.
Check the output risk too
Even a de-identified prompt can produce an output that exposes confidential logic or reconstructs sensitive details when combined with other context. Limit the requested scope and keep the result in an approved location. Do not paste a model’s answer into a public channel until it has been reviewed for confidential content.
Is this exact AI service approved for this use?
Verify the product, tier, account, and feature
Record the provider, product name, subscription or deployment tier, account owner, and feature you intend to use. Confirm that your organization has approved that exact combination for the data category and business purpose. An approved enterprise workspace does not make a personal account acceptable, and an approved text prompt does not necessarily cover file upload, image analysis, browser connectors, plug-ins, or third-party integrations.
Confirm who may use it
Access should be limited to people with a legitimate need to know. Use the organization-managed identity and approved workspace when policy requires it. Do not move a company document to a personal account merely because the personal account is easier to access.
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Check the purpose
Approval may be limited to defined activities such as drafting, coding assistance, or internal analysis. A service authorized for low-risk brainstorming may not be authorized for customer support, employment decisions, medical information, or regulated records. If the purpose changes, obtain approval again.
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Read the terms and privacy documentation for the exact product and account, and save the date and version or page you reviewed. Look for clear answers to each question below:
- Model improvement: Are prompts, files, feedback, or outputs used to train, fine-tune, evaluate, or otherwise improve models? Does an account setting change that practice?
- Retention: How long are prompts, files, conversation logs, safety records, and backups kept? Is retention different for deleted conversations or inactive accounts?
- Human or vendor access: Can employees, contractors, reviewers, or support personnel view submissions, and for what purposes?
- Disclosure and subprocessors: Which other companies receive or process the data, and for what functions?
- Deletion: Can your organization delete individual items or the account’s data? What exceptions apply for legal obligations, abuse prevention, security logs, or backups?
- Settings: Which controls must an administrator configure, and are they enabled by default?
- Ownership and responsibility: What does the contract assign to your organization, and what does it require the provider to do?
Do not infer a guarantee from a marketing phrase such as “private” or “secure.” Find the operative terms for your account and feature. If the provider’s documents do not answer a question important to your data, treat that gap as unresolved and escalate it.
What security and contract safeguards cover the service?
Require written commitments
For material company data, look for written requirements covering encryption and access control, retention and deletion, confidentiality, incident notification, subcontractors, audit or assurance evidence, and data location or transfers when those issues matter to your organization. The FTC recommends investigating a service provider’s security practices, putting expectations in contracts, and verifying that the provider follows them rather than relying only on assurances.
Check administrative controls
Determine whether the service supports centralized identity management, multi-factor authentication, role-based access, administrator audit logs, export controls, and the ability to disable risky features. Confirm who can change data-use settings and whether those changes are logged.
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Understand incident commitments
Find the contract’s definition of a security incident, notification deadline, communication method, cooperation duties, and responsibility for investigation. A general privacy statement may not provide the incident commitment your customer or regulatory contracts require.
Consider location and transfers
If your organization restricts where data may be stored or processed, verify the relevant locations and transfer terms for the product, backups, support access, and subprocessors. Do not assume that selecting a regional interface means every processing activity stays in that region.
Do policy, contracts, or law restrict the disclosure?
Check your organization’s acceptable-use, information-classification, records-management, procurement, and incident-response policies. Then check obligations attached to the information itself:
- A customer agreement may prohibit disclosure to a new processor or require advance notice.
- An employment or confidentiality agreement may restrict use of personnel or partner information.
- A privacy notice or consent may not cover sending data to a particular AI provider or using it for a new purpose.
- Sector-specific rules may impose requirements for access, minimization, location, retention, or human review.
- Records schedules may require preservation that conflicts with an AI service’s deletion behavior.
The applicable answer depends on the data, industry, contracts, jurisdictions, and purpose. Ask the privacy, security, legal, compliance, or records-management owner when any of those factors are uncertain.
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A practical pre-submission screening process
- Describe the task. State what the model must do and what output you need.
- Inventory the submission. Include prompts, files, conversation history, connected sources, and metadata.
- Classify the highest-risk content. Identify personal, customer, employee, secret, trade-secret, regulated, and contract-restricted information.
- Minimize. Remove fields, pages, rows, and context that are not required.
- Redact or synthesize. Replace identifiers and confidential examples; remove credentials and keys completely.
- Verify the exact service. Check the provider, product tier, account, feature, purpose, and authorized users against company policy.
- Read current terms. Record answers about training or improvement, retention, human access, sharing, subprocessors, deletion, settings, and transfers.
- Verify safeguards. Confirm written security, access-control, audit, incident-notification, and deletion commitments appropriate to the data.
- Obtain approval. Route exceptions and ambiguous classifications to the responsible internal owner.
- Submit only after the gate passes. Keep the approved, minimized version and avoid reintroducing removed details in follow-up prompts.
What should you record for an auditable decision?
A short record makes later review possible and prevents repeated guesswork. Capture:
- Date of the decision and the business purpose.
- Exact provider, product tier, account or workspace, and feature.
- Data categories present before redaction and in the final submission.
- What was removed, masked, or replaced.
- Terms and settings checked, including retention, model improvement, access, subprocessors, deletion, and transfers.
- Policy, contract, or legal requirements considered.
- Approver or owner who resolved the question.
- Any required configuration, retention limit, access restriction, or review of the output.
Record the date because provider terms, settings, and product features can change.
What if you already submitted data without approval?
Stop sending additional material and notify your organization’s security or privacy contact through the approved incident channel. Preserve the relevant prompt, file name, account, product, date, settings, and recipients so the owner can assess what was disclosed. Do not attempt a private workaround or delete evidence before the responsible team advises you.
Ask the provider, through the organization’s authorized administrator or contract contact, what deletion, access, and incident procedures are available. If credentials or keys were included, follow your organization’s secret-rotation process. Whether customers, regulators, or other parties must be notified is a decision for the organization’s legal, privacy, and security owners.
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Pause when any of these conditions applies:
- You cannot identify all information in the prompt, file, or connected context.
- The submission contains credentials, unredacted personal data, regulated information, trade secrets, or contract-restricted material that the service is not explicitly approved to handle.
- You are using a personal, unapproved, or differently configured account.
- The terms do not clearly explain retention, model improvement, access, sharing, deletion, or incident response relevant to your risk.
- No owner is available to approve an exception or interpret an obligation.
Use a lower-risk, approved alternative, remove more data, or wait for the responsible owner. Buying a governance or data-loss-prevention product can help enforce approved-use rules, but software does not make an otherwise unauthorized disclosure acceptable.
Who makes the final decision?
The employee preparing the prompt is responsible for stopping and asking when something is unclear, but does not have to interpret every legal or contractual issue alone. Managers confirm business need and approved workflow. Security owners evaluate technical controls and incidents. Privacy and legal owners interpret data-protection, confidentiality, and contract obligations. Records-management owners address retention and disposal. Procurement or vendor-management teams verify written provider commitments.
The safest final question is specific: “For this exact service, account, feature, purpose, and data category, may I submit this minimized material under our policy and contract?” If nobody can answer it confidently, the material is not ready to send.
Quick Recap
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