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The safest way to use several AI tools is to disclose as little as possible, classify every piece of information before sending it, remove identifying details, and use an approved business or enterprise system for confidential or regulated work. Privacy settings are provider-specific: disabling training or enabling a temporary mode in one service does not change what another service retains, reviews, or does with your data.
Public AI services may keep prompts, uploads, generated answers, memories, feedback, and data from connected applications. Use the workflow below to decide what may be shared, check each service’s controls, and clean up the data trail after the task.
What should you never paste into a public AI tool?
Do not enter personal, sensitive, regulated, or confidential information into a publicly accessible chatbot unless your organisation has explicitly approved that service and its terms for the data involved. The Centers for Medicare & Medicaid Services (CMS) states: “Never disclose or input PII, PHI, or any sensitive CMS data (including financial, health, vendor, procurement, evaluations, draft policies, or proprietary/business information) into publicly accessible AI platforms, chatbots, or prompts.”
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| Data class | Typical examples | Safe default |
|---|---|---|
| Public | Published articles, public documentation, released product descriptions | Usually suitable, after checking that no hidden comments, tracking data, or personal details are included. |
| Internal | Unpublished plans, internal procedures, non-public meeting notes | Use only a service approved by your organisation; remove names and commercially sensitive details. |
| Personal | Names, email addresses, phone numbers, account identifiers, exact locations | Redact or replace with realistic placeholders before submission. |
| Sensitive | Health information, financial details, identity documents, precise location history, information about children | Do not use a public tool. Use an approved system with documented protections. |
| Regulated | Protected health information, personally identifiable information, payment data, government records | Follow the applicable law, contract, and organisational policy; public chatbots are not an acceptable default. |
| Confidential or proprietary | Credentials, API keys, source code, vendor terms, draft policies, evaluations, trade secrets | Keep it out of public tools unless an explicitly authorised environment requires it and controls are verified. |
Even a document that looks harmless can contain hidden metadata, tracked changes, customer identifiers, or a secret in a code sample. Treat every upload as a disclosure, not merely as a temporary view.
What happens to information sent to several AI services?
Each service can create its own record of the same material. Depending on the provider and account type, prompts, uploaded files, outputs, memories, feedback, and connected-app data may be stored, reviewed by people for safety or quality, used for model improvement, or retained for legal, security, or operational reasons.
OAIC notes that privacy obligations apply both to personal information entered into AI systems and to outputs that contain personal information. The UK Information Commissioner’s Office (ICO) says privacy information should explain the processing purposes, retention periods, and who receives the data. A tool’s attractive interface does not remove those obligations.
Copying an answer from one chatbot into another creates a second disclosure. The second provider does not inherit the first provider’s deletion request, training opt-out, regional terms, or contractual protections. Re-run the data-classification and redaction checks every time information crosses a service boundary.
How do I classify data before starting an AI task?
Make classification a deliberate first step rather than something you decide while typing. A short preflight prevents accidental disclosure when a prompt grows to include examples, attachments, or copied email threads.
- Describe the task without data. Write what you want the model to do, such as summarize, rewrite, classify, or debug. This reveals whether the task really needs the underlying personal or confidential material.
- Mark the highest sensitivity present. If a paragraph contains both public text and a customer account number, classify the submission as personal or sensitive, not public.
- Check ownership and permission. Confirm that you are allowed to process the material and that the provider is approved for that class of data.
- Decide whether a synthetic example works. For drafting, coding, and analysis, invented names, values, and records often provide all the context the model needs.
If you cannot explain why a particular field is necessary, leave it out. A useful prompt can usually specify format, constraints, and the desired outcome without exposing the original identity of a person or organisation.
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How can I redact prompts and files effectively?
Redaction should remove direct identifiers and details that can identify someone when combined. Replacing a name with a token is safer than merely masking a few characters.
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Remove or generalise identifiers
- Replace names with role labels such as
[customer]or[employee]. - Remove account, policy, invoice, ticket, and identification numbers; keep only a non-identifying category if needed.
- Generalise exact addresses and dates to a city, region, month, or age range when precision is not required.
- Delete phone numbers, email addresses, usernames, device identifiers, and unique URLs.
- Strip health details, financial information, legal records, and information about children unless an approved system explicitly requires them.
- Remove passwords, private keys, session cookies, access tokens, database connection strings, and secrets from code or logs.
Check the file, not just the visible text
Before uploading a document, accept or remove tracked changes, comments, hidden sheets, embedded objects, author names, and document properties. In spreadsheets, inspect every worksheet and formula; in logs, remove headers and tokens as well as the message body. If the task is summarisation, paste a short redacted excerpt instead of the original file.
Keep replacements consistent
Use stable placeholders when the model must follow a person or event through a document. For example, replace one person with PERSON_A everywhere, but do not keep a private lookup table in the same chat or upload it later. If re-identification is possible from a rare job title, date combination, or small location, generalise those attributes too.
Which privacy controls should I compare across AI tools?
Compare documented controls rather than relying on a “private” label. The important question is what each control covers, for which account type and region, and what exceptions remain.
| Control | Questions to ask | Why it matters when using multiple tools |
|---|---|---|
| Model-training use | Are prompts, files, and feedback used to improve models by default? Does an opt-out cover future activity only? | A training choice in one service has no effect on another service. |
| Temporary or incognito mode | Does the mode prevent history and memory creation? How long can safety or abuse records remain? | “Temporary” often limits product features without meaning immediate deletion. |
| Chat and file retention | How long are conversations and uploads stored, and are legal or safety exceptions listed? | Re-uploading the same file can create several independent retention periods. |
| Memory and personalisation | Can the service save facts about you, and can you inspect and delete them separately from chats? | Deleting a conversation may not remove a saved memory. |
| Human and safety review | Can staff or contractors inspect content for safety, quality, or abuse investigations? | Review exceptions can apply even when model training is disabled. |
| Connected applications | What can connectors read, and can they continue to supply data in later chats? | An enabled connector can disclose more than the text you intentionally paste. |
| Deletion and export | Can you delete chats, files, memories, and shared links individually? What remains after deletion? | You need a cleanup path at every provider, not just at the account level. |
| Contract and region | Do business or API terms differ from consumer terms, and where is data processed? | Account type, age, geography, and plan can change the protection you receive. |
What privacy settings are available in ChatGPT?
For personal ChatGPT accounts, open Settings > Data Controls and turn off Improve the model for everyone if you do not want new conversations used to improve models. Those conversations remain in your history; turning the setting off does not delete earlier chats.
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What does Temporary Chat do?
Temporary Chats do not appear in history, do not create or update memories, and are not used to improve models. OpenAI says they may nevertheless be retained for up to 30 days for safety. Use the mode to reduce persistence, not as a promise that content disappears immediately.
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What about business products and the API?
OpenAI says its business products and API do not train on inputs and outputs by default, subject to their terms and any explicit opt-in. Confirm the exact product, contract, region, and administrator settings before sending confidential material; a consumer account and an organisation-managed account are not interchangeable.
What privacy settings are available in Microsoft Copilot?
Microsoft provides controls for personalisation and memory, training on conversation activity, voice-training activity, personalised advertising, and deletion. Review each control in the account’s privacy settings rather than assuming that one opt-out covers every use.
How long is Copilot history kept?
Microsoft Support says Copilot conversation history is retained for 18 months by default. Check whether your account, region, or administrator policy changes that period, and delete conversations or other stored data when the task is complete.
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No. Microsoft says opting out of model training excludes future conversation activity from training but does not necessarily disable other product-improvement, advertising, safety, security, or compliance uses. Read the scope of each setting and verify what happens to previously collected activity.
How should I move work from one AI tool to another?
Handle every hand-off as a fresh disclosure. An answer that was safe to copy may contain a person’s name, a quoted document, a hidden identifier, or a confidential inference that was not present in your original prompt.
- Inspect the output. Search for names, numbers, email addresses, code secrets, internal project names, and verbatim passages before copying.
- Remove unnecessary context. Keep only the portion needed for the next task; do not forward the entire chat transcript or original attachment.
- Reclassify the material. Treat generated text containing personal information as personal information, even if the model produced it.
- Check the destination service. Review its training, retention, memory, review, connector, and regional terms before pasting.
- Use a clean transfer format. Prefer a short redacted summary or synthetic record over a direct export of the first conversation.
- Delete intermediate copies. Remove shared links, exported files, and temporary documents from both services when they are no longer needed.
How do connectors and file permissions create extra risk?
Connectors can expose information without a new copy-and-paste action. A connected mail, drive, calendar, code repository, or business system may be searched by the model according to the permissions granted to the account.
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- Enable a connector only for the task that requires it.
- Grant the narrowest available scope and avoid broad workspace access.
- Review which files, messages, or records the connector can reach before asking a question.
- Disable the connector after the task and review recent access logs where available.
- Do not assume that deleting a chat revokes the connector’s standing permission.
If a task can be completed with a redacted excerpt, use that instead of authorising an entire application. Connector access should be treated like a separate data-processing decision.
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Cleanup is part of privacy protection. Follow the provider’s documented deletion controls and note that legal, safety, security, or compliance exceptions may delay permanent removal.
- Delete the conversation and any uploaded files.
- Delete saved memories or personalisation entries separately if the service stores them.
- Remove public or shared links to the conversation.
- Turn off or revoke connectors that are no longer necessary.
- Clear local downloads, copied transcripts, exports, and temporary working files.
- Record what was shared if the material was personal, regulated, or covered by an organisational retention rule.
For ChatGPT, disabling model improvement does not erase existing chats. For Copilot, the 18-month default history period is not a substitute for deliberate deletion.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should an organisation document before employees use several AI tools?
Organisations need a written, reviewable policy rather than a list of preferred chatbots. The policy should match data classes to approved services and explain who is accountable for exceptions.
- Approved tools and accounts: identify permitted consumer, business, and API products, including the regions and plans covered.
- Permitted data classes: state whether public, internal, personal, sensitive, regulated, or confidential information may be entered.
- Retention and deletion: specify how chats, files, memories, exports, and shared links are handled.
- Connector rules: require least-privilege permissions, approval, and periodic review.
- Training and awareness: teach redaction, synthetic examples, prompt hygiene, and the difference between generated content and verified facts.
- Incident reporting: provide a route for employees to report accidental disclosure, suspicious connector access, or a provider-policy change.
- Periodic review: recheck provider settings, terms, retention periods, and regional requirements because they change.
The Federal Trade Commission has said that model-as-a-service companies must abide by commitments made to customers, regardless of how or where those commitments were made. Keep copies of relevant contractual promises and privacy notices so an administrator can verify that the service still meets policy.
What if I already sent sensitive information to an AI tool?
Act quickly and preserve enough information to assess the incident. Do not paste the sensitive material into another chatbot while trying to get help.
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- Stop further sharing and disable any connector involved.
- Delete the affected chats, uploads, memories, and shared links using the provider’s controls.
- Rotate exposed passwords, API keys, access tokens, or certificates immediately.
- Notify your privacy, security, legal, or compliance contact according to organisational policy.
- Record the service, account type, date, data categories, recipients, and deletion request.
- Ask the provider what deletion, safety retention, review, and contractual processes apply.
- Monitor affected accounts and systems for misuse, and follow any required notification process.
Deletion can reduce future exposure but cannot undo a disclosure that has already been viewed, copied, or incorporated into another system. Treat the event as a potential privacy incident when the data was personal, regulated, or confidential.
Is there one AI chatbot that is safest for sensitive information?
No single chatbot is universally safest. Protection depends on the data, account type, contract, region, retention rules, connector permissions, human-review terms, and the controls you actually configure.
The available guidance does not identify a physical product that protects privacy across multiple AI tools. A privacy screen, security key, password manager, or encrypted drive can address other device or account risks, but none replaces data minimisation and provider-specific controls. Choose an approved environment whose documented terms match the sensitivity of the work, and verify those terms again when the service changes.
Frequently Asked Questions
Can a VPN keep my AI conversations private?
A VPN can hide some network details from the local network or internet provider, but it does not prevent the AI service from receiving, retaining, reviewing, or using the prompts and files you submit. Treat network privacy and provider data handling as separate controls.
Should I create separate accounts for different AI services?
Separate accounts can limit how much profile information is shared across providers and make deletion or access reviews easier. They do not make sensitive prompts safe by themselves; each account still needs the right training, retention, connector, and regional settings.
Does encrypting a file before upload make it safe to share with a chatbot?
Encryption helps only if the service cannot decrypt the file. Uploading a password-protected archive while sending the password in the same chat defeats that separation, and an encrypted file may also be unusable to the model. Use an approved workflow designed for confidential files instead of relying on encryption alone.
How can I tell when an AI provider has changed its privacy terms?
Check the provider’s privacy notice, data-controls page, and account settings on a scheduled basis, and keep the date and version of the terms used for important work. Organisations should subscribe to provider notices or assign an owner to review changes before a tool remains approved.
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