Keep secrets, regulated personal information, identifiable customer or employee records, payment and banking details, health information, confidential contracts, trade secrets, unpublished financials and proprietary code out of any general-purpose AI tool unless your business has approved the exact workflow and checked the provider’s retention, training, access, deletion and contractual controls. For ordinary drafting or brainstorming, use a minimized or synthetic example instead. Treat every prompt, upload and generated file as a business data flow that needs an owner, access controls and a deletion plan.
The information that should never go into an unapproved AI chat
A prompt is a disclosure. It can be retained by the provider, copied into application logs, exposed through a shared workspace, recorded in browser history or viewed by anyone who later obtains access to the account. The safest default for a small business is simple: if disclosure could harm a customer, employee, patient, partner or the company, do not enter it into an unapproved chatbot.
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Credentials and technical secrets
Never paste passwords, passkeys, multifactor-authentication codes, API keys, private keys, recovery codes, session tokens or database connection strings. This includes secrets hidden in stack traces, configuration files, screenshots and copied logs. A request to “find the bug” does not make a credential safe to share. Replace the secret with a token such as API_KEY_REDACTED, rotate the original if it was exposed, and provide only the surrounding error text needed for diagnosis.
Direct identifiers and financial records
Keep Social Security numbers, passport and driver-license numbers, full dates of birth, bank-account and routing numbers, payment-card numbers, tax IDs, credit reports and account statements out of general-purpose tools. The Federal Trade Commission (FTC) specifically identifies Social Security numbers, credit-card and other financial information, account numbers and credit reports as sensitive categories in its business privacy guidance.
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Do not upload patient or client records, diagnoses, treatment details, insurance identifiers, disability information, biometric data, precise location or children’s data. A model provider may receive the entire text surrounding the field you intended to ask about, so removing one name is not enough when dates, rare conditions or narrative details can identify the person. The FTC has warned that model-as-a-service providers may receive health and financial data and must honor the privacy commitments made to users.
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HR investigations, payroll records, performance notes, disciplinary material, customer-support transcripts, complaints and identity-verification documents belong in approved systems with defined access rights. An employee’s name is not the only identifier: job title, shift, location, dates and a distinctive incident can make a person identifiable. Use an invented case with the same structure when you need help drafting a process or response.
Confidential business information
Keep contracts, non-public pricing, supplier terms, acquisition plans, source code, security findings, product roadmaps, unreleased designs, trade secrets and credentials embedded in logs out of unapproved tools. Internal documents and competitively significant business data are exactly the kind of information the FTC says users may reveal to model-as-a-service companies. A confidentiality clause with a customer or supplier can also prohibit disclosure to a third-party AI service, even when no privacy law is involved.
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Why “the provider does not train on your data” is not enough
Training is only one possible use. A provider can retain prompts for a limited period, send them to human reviewers, disclose them to subprocessors, store them in another region, include them in abuse-monitoring systems or make them available to workspace administrators. Deletion may be unavailable, delayed or limited to the primary account. Export and backup copies can create additional retention.
FTC guidance, including “AI Companies: Uphold Your Privacy and Confidentiality Commitments” (2024), says companies must honor privacy promises and can face enforcement for secret or undisclosed uses. Read the complete terms, privacy notice, data-processing addendum and security documentation that apply to the specific plan your business would buy. Marketing language is not a substitute for a contractual commitment.
A five-step approval process for any AI tool
- Inventory the data flow. Record what will be sent, from which system, by whom, to which feature, where it is stored, who can access it, how long it is retained and whether it is used for training or product improvement. Include attachments, browser extensions, plug-ins, connected drives and generated outputs. NIST’s Risk Management Framework Small Enterprise Quick Start Guide (published July 2024) supports this kind of documented risk inventory.
- Minimize before sending. Remove identifiers, secrets, unnecessary fields, exact dates and hidden metadata. Crop screenshots, strip document properties and copy only the passage needed for the task. If synthetic examples can produce the same answer, use them. The FTC’s business guidance says to keep only information the business needs and dispose of it securely when the need ends.
- Match promises to the contract. Confirm retention periods, training and product-improvement use, human review, subprocessors, deletion, export, regional storage and breach-notification duties. Establish which terms apply to free, consumer, team and enterprise editions; defaults can differ. Document the answer and the plan version, not just a salesperson’s statement.
- Control access and accountability. Use a business workspace rather than personal accounts, assign least-privilege roles, require administrator review for connectors and uploads, and name an owner for incidents and deletion requests. Keep an inventory of approved tools and prohibit unapproved browser extensions or shared logins. The FTC and NIST both recommend limiting access to people who need it and managing privacy risk through governance.
- Protect the account. Require multifactor authentication everywhere it is available, use a password manager for unique passwords and prefer a phishing-resistant physical security key where practical. CISA describes a physical security key as the strongest option in its listed MFA methods; NIST’s small-business MFA page was updated January 5, 2026. MFA limits account takeover, but it does not make a sensitive prompt safe: account security and prompt privacy are separate controls.
How to redact information without creating false confidence
Redaction is useful only when the remaining text cannot reasonably identify a person or reveal a secret. Replacing “Maria Lopez” with “Employee A” fails if the document still says she is the only night-shift manager in a named town and describes a unique incident on a known date.
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A practical redaction sequence
- List every field that can identify a person, account or business relationship: names, email addresses, phone numbers, addresses, IDs, dates, locations, account numbers, filenames and distinctive quotations.
- Replace each with consistent placeholders, such as
EMPLOYEE_01,CUSTOMER_07,DATE_AandVENDOR_X. Keep the mapping offline; never paste the lookup table into the AI tool. - Generalize rare values. Change an exact birth date to an age range, a precise address to a region and a unique transaction amount to a rounded band when that preserves the task.
- Remove metadata and embedded content. Check document properties, tracked changes, comments, hidden spreadsheet tabs, EXIF data, hyperlinks and screenshots of other applications.
- Review the redacted version as an outsider. Ask whether someone with ordinary business knowledge could infer the person, account, secret or deal. If yes, use a synthetic example or do not send it.
For code and logs, remove keys, tokens, hostnames, internal URLs, customer identifiers and proprietary algorithms. Preserve the error class, relevant function names and a fabricated sample value so the model can still reason about the problem.
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Not by default. Customer data may be used only through a workflow your business has approved after checking the applicable plan’s retention, training, access, deletion, regional-storage and contractual terms. Even then, send the minimum necessary fields, restrict the workspace, record the purpose and set a deletion deadline. If you cannot answer who can access the prompt, how long it remains and how to delete it, do not upload it.
A support agent asking an AI tool to summarize a complaint can usually work from a synthetic transcript or a version with identifiers removed. If the exact record is necessary, route it through an approved system with documented privacy and security controls rather than copying it into a personal account.
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Is it safe to upload employee records?
Assume no unless the specific record, purpose and tool have been approved. Payroll, health accommodations, disciplinary notes and investigation files carry employment, privacy and sometimes regulatory obligations. Limit access to the smallest group, define a retention period, prohibit reuse for model training unless expressly authorized, and provide a way to remove the data and outputs. An AI-generated summary is still a copy of the underlying employee information and must receive the same protection.
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Put the answers in writing and tie them to the edition and contract your business will use.
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| Control area | Question to answer | Evidence to keep |
|---|---|---|
| Training and improvement | Are prompts, files or outputs used to train or improve models by default, and can an administrator disable that use? | Current terms, setting screenshot and contract clause |
| Retention | How long are inputs, outputs, logs, backups and abuse-monitoring records kept? | Retention schedule and deletion procedure |
| Human review and subprocessors | Can staff or subcontractors view content, for what purpose and in which countries? | Privacy notice, subprocessor list and access policy |
| Deletion and export | Can the business delete individual items, an entire workspace and provider backups, and export its data? | Documented workflow, service-level terms and test record |
| Geography and incidents | Where is data stored and processed, and how quickly will the provider notify you of a breach? | Regional-storage terms and breach-notification clause |
| Access and audit | Are SSO, MFA, role-based permissions, audit logs and connector controls available? | Administrative documentation and an access review |
| Security and regulation | What encryption, compliance commitments and data-processing terms apply to your obligations? | Security documentation and signed data-processing agreement |
If an answer is “not stated,” treat that control as unresolved rather than assuming the most favorable interpretation. An enterprise plan may offer administrative data controls, but the label alone does not establish a particular retention or training policy.
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What a small-business generative-AI policy should say
A workable policy can be short, provided it is specific:
- Only approved tools and business accounts may be used for work.
- Never enter credentials, regulated personal data, identifiable customer or employee records, payment information, health information, confidential contracts, trade secrets, unpublished financials or proprietary code unless the workflow is expressly approved.
- Use synthetic or redacted data, minimize fields and remove metadata before submission.
- Do not connect drives, email, CRM, HR or code repositories without administrator approval and a documented data-flow review.
- Enable MFA, use unique passwords and prohibit shared accounts.
- Label AI-generated output for human review; do not treat it as an authoritative record.
- Report accidental disclosure immediately, preserve relevant logs and rotate exposed credentials.
- Review approved tools, provider terms and access lists at a defined interval and when the provider changes its terms.
If someone has already pasted sensitive information
- Stop further sharing and preserve the prompt, account, workspace and timestamp as evidence.
- Revoke or rotate every exposed password, key, token, recovery code or connection string. Treat a secret as compromised even if the message was deleted.
- Restrict access to the affected workspace, remove shared links and disable connectors that could expose more data.
- Contact the provider through its security or privacy channel to request deletion, determine retention and identify subprocessors or reviewers who accessed the content.
- Assess whether customers, employees, regulators, insurers or contractual partners must be notified. Follow the obligations that apply to your location and industry.
- Record the cause and update the approved-tool list, training, redaction checklist and incident procedure.
Secure disposal matters after the immediate incident as well. The FTC’s business guidance captures the principle plainly: “If it’s not in your system, it can’t be stolen by hackers.” Keep only what the business needs, then delete it through a controlled process.
A decision test employees can use in seconds
Before pressing send, ask: Would I be comfortable giving this exact text to an unknown contractor, storing it in a third-party log and explaining the disclosure to the person named in it? If the answer is no, stop. Remove the sensitive fields, create a synthetic example or use an approved internal workflow. That pause protects more effectively than relying on a provider’s headline privacy claim.
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