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Do not put sensitive information into an AI tool unless the specific product, account, connected features, and your organization’s rules allow it. First ask whether you can complete the task with less data. Remove identifiers and confidential details that are not needed, check where the information may go, and confirm how the exact service handles access, model improvement, retention, and deletion. If a law, contract, or workplace policy bars disclosure, get the required approval before sharing anything.

Start by deciding whether the data belongs in the tool at all

AI tools can make it easy to paste a document, attach a file, or connect a work account. That convenience does not establish that the service is approved for the information in it. A sensible default is to treat sensitive material as prohibited until you have checked the exact service and account and confirmed that its use is permitted.

Before entering a prompt or attaching a file, identify what the material contains and what the task actually requires. A question about the wording of one paragraph may not require the full contract; a request to explain an error may not require a complete source repository. Reducing the amount of data also reduces the amount that could be exposed through a mistake, an unexpected integration, or a retention setting.

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  • Stop and seek approval if the material is restricted by a customer agreement, confidentiality obligation, privacy requirement, security policy, or applicable law.
  • Use an approved service and account when workplace rules require one. A personal login is not interchangeable with a managed workspace or an approved API.
  • Minimize and de-identify information when the task can be done without real names, account details, or unique identifiers.
  • Do not submit credentials such as passwords, API keys, access tokens, recovery codes, or private keys in an ordinary prompt.

These are practical safeguards, not a legal determination for every jurisdiction or data type. Requirements can vary according to the information, the purpose, where it is processed, and the agreements that apply.

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Classify what you plan to share

Review the complete material, not just the words you intend to type. An attachment, screenshot, code sample, retrieved file, or connected source can contain information that the prompt does not mention. Context matters: details that look harmless alone may identify a person or disclose confidential facts when combined.

Category to check What to look for Practical decision
Public Information already intended for unrestricted public release. Confirm that the actual copy contains no private notes, hidden metadata, or unreleased material.
Internal Work information intended for colleagues or approved systems, but not necessarily for public disclosure. Check your organization’s acceptable-use rules and the account’s approval status.
Confidential Business plans, customer information, contracts, unreleased work, or other nonpublic material. Use only if the service and workflow have been approved for that information.
Personal or regulated Information about an identifiable person, or data subject to a specific privacy or regulatory requirement. Check the applicable policy, purpose, permissions, and required approval before disclosure.
Credential-bearing or security-sensitive Passwords, keys, tokens, recovery codes, private keys, or details that could enable access or exploitation. Do not include in an ordinary prompt; use an approved secrets-management process where access is necessary.

This is a screening aid, not a substitute for your organization’s official classification scheme. NIST’s guidance on personally identifiable information (PII) emphasizes context-based protection. Its 2010 SP 800-122 also warns that AI can create new re-identification risks or reveal additional insights about people. A dataset with names removed may therefore remain sensitive if other details can identify someone.

Trace where the information can go

Consider the information lifecycle, not only the prompt box. The relevant questions include who can access the submitted material, what service receives it, whether a connected feature can retrieve additional information, how long records are retained, and what deletion removes. The Federal Trade Commission (FTC) advises businesses to understand how personal information moves into, through, and out of an organization to assess vulnerabilities.

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  1. Identify the source. Is the material typed by you, attached from a device, drawn from a work drive, or retrieved from another connected service?
  2. Identify the account and product. Is this a personal account, managed workspace, organizational assistant, API, or an agent built on another service? Different terms and controls can apply.
  3. Check the access path. Find out whether the tool can use organizational sources or connected apps, what permissions it relies on, and whether it can retrieve more than the text you entered.
  4. Check the lifecycle controls. Review model-improvement settings, retention, deletion, history, administrator controls, and any contractual commitments relevant to the use.
  5. Record the decision when required. Follow your organization’s review and approval process, particularly for recurring workflows or restricted categories of data.

Microsoft says organizational Copilot can use organizational data available through Microsoft Graph, subject to a user’s permissions. That means a prompt can lead to use of data beyond the words typed. Review source permissions and connected features rather than assuming the prompt is the only information in play.

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Minimize the prompt and its attachments

Once a use is allowed, share only what is needed to answer the question. The FTC recommends collecting only information necessary for a business purpose and disposing of it when there is no longer a business need. Applied to AI use, minimization starts before submission: do not upload a full dataset or file when a narrow excerpt will do.

Replace identifiers with neutral labels

When real identities are irrelevant, substitute labels such as [customer], [account], or [employee]. Remove email addresses, phone numbers, customer IDs, account numbers, addresses, and unique details that do not affect the answer. Keep a separate mapping only if the task genuinely requires restoring identities later, and store that mapping according to your organization’s rules.

Trim the material to the task

  • For a writing question, provide the relevant paragraph rather than the entire confidential report.
  • For a data question, share the necessary columns and a small representative sample rather than a complete customer export.
  • For a code question, isolate the relevant function and replace secrets, internal hostnames, and unrelated business logic.
  • For a screenshot, crop unrelated windows, notifications, names, account details, and background information.

Use synthetic or generalized examples when they can support the same task. Do not assume that deleting a name makes a case anonymous: dates, locations, job titles, rare events, or combinations of attributes may still point to a person.

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Keep secrets out of ordinary prompts

Passwords, API keys, access tokens, recovery codes, and private keys should not be pasted into a general-purpose chat to make a task easier. If a workflow needs a credential, use the organization’s approved secrets-management and access-control process. Minimizing sensitive inputs and restricting access are basic security practices; a model-training setting does not make it safe to disclose a secret.

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Verify the exact product, account, and configuration

“The AI tool” is not a sufficiently precise security description. Consumer chat, a managed business workspace, an API, a workplace assistant, and an agent connected to other applications may have different terms, controls, and data flows. Confirm the configuration that will actually handle the information—not merely the vendor’s general reputation or a product-family statement.

For the particular workload, check:

  • Account and contract: Which account type is signed in, which terms apply, and whether your organization has an agreement covering this use.
  • Model improvement: Whether prompts, responses, files, feedback, or other feature data may be used to improve or train models, and whether a setting covers the feature you intend to use.
  • Retention and deletion: How long chats, files, logs, and backups are retained; what can be deleted; and whether deletion applies to each relevant data type.
  • Permissions: Which organizational information the service can retrieve and whether identity permissions and sensitivity labels are respected.
  • Integrations and agents: What data scopes they request, which sources they can access, what third-party terms apply, and what administrator controls are available.
  • Governance and location: Whether audit, sharing, retention administration, data location, processing, and contractual commitments fit the organization’s requirements.

Microsoft documents plan-dependent differences in organizational Copilot controls. OpenAI’s documentation distinguishes personal ChatGPT settings from managed-workspace controls. Confirm the current plan, contract, location, data residency, access model, and retention configuration for your own use; a brand-level claim cannot establish that every feature or data category is appropriate.

What the documented ChatGPT controls mean

OpenAI says eligible personal ChatGPT users can turn off “Improve the model for everyone” for new conversations. Turning it off prevents those new conversations from being used for model improvement, but does not remove them from chat history. If you want to keep history while disabling model improvement, those are separate controls: changing the improvement setting does not delete saved chats, and chats must be deleted separately when deletion is intended.

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OpenAI states that content from Business, Enterprise, Edu, Healthcare workspaces, and API use is not used to train models by default. “By default” is not a substitute for checking the account, workspace, administrator settings, applicable terms, or a particular feature’s handling. Temporary chats have separate handling and may be retained for safety purposes for up to 30 days while temporary. Verify current behavior and terms before relying on any setting.

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These details describe the product categories and settings stated by OpenAI; they are not a universal guarantee about other features, connected services, or every account configuration. For a workplace account, the administrator may control features and data, including access, retention, export, and deletion. Check with the administrator if you cannot confirm the controls or account type yourself.

What organizational Copilot protections do—and do not—establish

Microsoft’s enterprise data-protection documentation for organizational Copilot and Copilot Chat describes protections under Microsoft’s Data Protection Addendum (DPA) and Product Terms. Microsoft says prompts and responses are encrypted at rest and in transit, tenant isolation is provided, and identity permissions, sensitivity labels, retention policies, and audit apply. Microsoft also says prompts, responses, and Microsoft Graph data accessed through Copilot are not used to train foundation models.

Microsoft notes that controls vary by subscription. Web-search queries and agents may have distinct terms or handling, and an agent needs its own review of terms, privacy statement, permissions, and data access. Do not assume that protections stated for an organizational Copilot use automatically cover every connected feature or third-party agent. Check the relevant plan and terms, and keep access permissions appropriately limited.

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Review integrations and connected agents separately

A connection can create a second route to sensitive information. An AI assistant linked to work files, email, calendars, code repositories, or business applications may retrieve material based on the user’s permissions. An agent may also have its own provider, instructions, or requested scopes. The fact that a person can access a file does not automatically mean every AI feature should be allowed to process it.

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  1. Use only integrations and agents approved by your organization.
  2. Read the agent’s terms and privacy statement, and check the specific permissions or scopes it requests.
  3. Limit access to the sources and actions needed for the task; remove permissions that are not required.
  4. Confirm whether the agent’s handling is covered by the main service’s contract and controls or by separate terms.
  5. Review access when the workflow changes, the agent changes, or the permissions are no longer needed.

For organizational Copilot, Microsoft describes use of Microsoft Graph data subject to the user’s existing permissions. That makes careful permissions and source review important even when data is not being used to train foundation models.

Use a controlled workflow before, during, and after a task

Before you start

  1. Classify the prompt material, attachments, screenshots, code, and any context available through connected sources.
  2. Check acceptable-use, data-handling, and retention rules. If a contract, privacy obligation, security policy, or law may restrict disclosure, obtain the required approval.
  3. Verify that you are using the intended account and product. For managed accounts, ask the administrator about controls you cannot inspect.
  4. Confirm the exact service’s terms and configuration for model improvement, retention, deletion, access, integrations, and organizational coverage.

While composing and reviewing

  1. State the task without including sensitive background that is not necessary to answer it.
  2. Replace identities and unique details with neutral labels where possible, and share an excerpt or synthetic example instead of a full file.
  3. Inspect attachments and connected sources for information beyond the visible prompt. Avoid credentials in ordinary prompts.
  4. Check the response before copying it into a sensitive system or taking a consequential action. AI output may be inaccurate or unsafe; input confidentiality is only one part of responsible use.

After the interaction

  1. Apply the organization’s retention schedule and use the service’s retention and deletion controls when appropriate.
  2. Distinguish deleting a chat from changing model-improvement settings. Follow the relevant control for each purpose.
  3. Report an accidental disclosure through the organization’s incident process rather than assuming that deleting a visible chat resolves it.

The FTC recommends a written information-retention policy that specifies what to keep, how to secure it, how long to retain it, and how to dispose of it. NIST SP 800-122 includes incident-response planning among its recommendations for protecting PII. Follow your organization’s incident instructions promptly if information was shared in error.

Compare options using the same questions

When deciding whether a tool or plan is suitable, compare actual configurations rather than marketing labels. Use the same workload and data categories in the review so that a feature with stronger safeguards in one area does not obscure a gap in another.

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Decision area Questions to answer
Account and agreement Is this personal, business, enterprise, API, or a managed workspace? Which terms and organizational agreements apply?
Model improvement Can prompts, outputs, files, feedback, or feature-specific data be used for improvement? Does the selected setting cover the intended feature and account?
Retention and deletion How long are chats, files, logs, and backups kept? What does deletion remove, and what remains under the applicable terms?
Data access Can the service retrieve organizational data? Does it respect identity permissions and labels? Which connected sources are in scope?
Agents and integrations What permissions are requested? Are third-party terms involved? Can administrators restrict or audit use?
Administration and audit Can the organization enforce policy, manage retention and sharing, review activity, and follow an incident process?
Geography and compliance Where is data processed or stored? Which laws, contractual commitments, and workload-specific requirements apply?

If a material answer is unknown, treat that as an unresolved approval question rather than assuming the most favorable setting. Ask the service administrator or the organization’s security, privacy, or legal contact to confirm it before the sensitive use.

What to do if sensitive information was submitted by mistake

Act promptly and follow your organization’s incident-reporting procedure. Do not rely on deleting a chat as proof that every copy, log, connected source, or downstream record is gone; the available deletion behavior depends on the service and account. Similarly, turning off model improvement is not the same as deleting existing history.

  • Notify the appropriate internal security, privacy, or incident-response contact and describe what was shared, which account and feature were used, and when.
  • Use available service controls to delete the interaction or revoke an unnecessary integration, while preserving information needed for the incident review.
  • Follow the organization’s directions about credential rotation, customer or regulator notification, and recordkeeping; do not make those decisions from a generic AI-tool guide.
  • Review how the disclosure happened and adjust permissions, approved-use guidance, or workflow controls to reduce the chance of recurrence.

Keep the decision proportional to the data and task

A low-risk prompt built from public facts does not require the same review as an identifiable customer record or confidential source code. But the distinction must be made using the full context and actual account configuration. The safest useful workflow is to share the least information necessary, use an explicitly approved service and feature, restrict connected access, understand retention and deletion separately, and escalate uncertainty before disclosure.

NIST SP 800-122, published in 2010, remains foundational guidance for context-based protection of PII; its central principle is that PII should be protected from inappropriate access, use, and disclosure. FTC guidance adds the operational discipline of inventorying information, understanding its flow and access, retaining it only as needed, and disposing of it securely. Those practices provide a baseline, not a universal legal conclusion or a guarantee that a particular AI use is suitable.

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