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Protect sensitive data by keeping it out of public AI chats unless your organisation has approved the use, reduced the data to what the task needs and assessed the privacy risks. For work use, first identify the exact product and feature, then verify its contract, retention, training-use terms and administrator access. The name “Claude” alone does not tell you how a particular conversation will be handled.
What counts as sensitive data in an AI chat?
Sensitive data includes information that could expose a person, account, organisation or system if it were disclosed or reused. Anthropic’s consumer guidance specifically cautions against sharing financial details such as Social Security numbers, card numbers and bank-account details; health or medical information; passwords and private login credentials; and confidential business or personal documents. Treat these as prohibited by default in consumer chats.
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That rule should also cover data that seems harmless in isolation but becomes identifying when combined: a case number, a distinctive job title, a narrow location, a specific date or a private URL. A document can contain personal information in its text, tables, comments or attachments, even when its visible first page appears routine. Assess the whole material you intend to provide, not just the sentence you plan to ask about.
Use a classification before you prompt
Before opening an assistant, classify the material as public, internal, confidential, personal, regulated, a credential or a secret. Your organisation may define these categories differently; follow its policy where one exists. A useful default is that public information may be considered for a prompt, internal information needs an approved use, and personal, regulated, confidential or secret material needs explicit review rather than casual experimentation.
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Information can fall into more than one category. A customer complaint may be both confidential and personal; a spreadsheet may include ordinary business figures alongside account identifiers. Apply the stricter handling rule to mixed material, or separate the safe portion from the restricted portion before use.
Why is a public AI assistant a privacy risk?
A prompt is information you disclose to a service, not simply a private note on your device. Privacy obligations can apply both to personal information entered into an AI system and to personal information returned in its output. The Office of the Australian Information Commissioner (OAIC), in guidance updated 17 January 2025, says the Privacy Act applies to all uses of AI involving personal information and recommends that organisations avoid entering personal information—particularly sensitive information—into publicly available generative-AI tools because of the significant and complex privacy risks.
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That is Australian regulatory guidance, not a statement that the same law governs every reader. The practical lesson is broader: a privacy decision should account for the complete path of information through the product, the organisation’s obligations and the possible consequences of disclosure. Encryption and access restrictions can reduce exposure, but they do not by themselves establish that a particular use is appropriate.
Risk also arises from the answer. An assistant may repeat personal or confidential text from the prompt, combine details into a more revealing summary or infer sensitive traits. A response is not automatically safe to forward just because the assistant generated it.
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How do Claude’s product surfaces differ?
Claude consumer chat, Claude for Work, the Claude API and deployments through cloud providers have different control and retention arrangements. Confirm the surface, account, workspace and feature you are using; do not infer the handling of one from the name of another.
| Surface | What the available documentation says | What to verify before using sensitive material |
|---|---|---|
| Consumer Free, Pro and Max | Anthropic says data is encrypted in transit and at rest, employee access is limited by default, and controlled access can occur for feedback or trust-and-safety enforcement. Consumer privacy settings and product retention practices apply. | Check the current consumer settings and retention terms. These protections do not make pasting highly sensitive data advisable. |
| Claude for Work | Under the commercial terms described by Anthropic, the customer organisation is controller and Anthropic is processor. The organisation controls membership and can access or export user-submitted conversation history. Anthropic says it does not use customer data to train generative models under those terms. | Confirm the current contract and data processing agreement (DPA), region, subprocessors, administrator access, training-use terms and export and deletion rights. |
| Claude API | Anthropic documents zero-data-retention (ZDR) and HIPAA-ready arrangements for eligible customers and features. Retention depends on the feature; some functions require it. Anthropic says retained data is not used for model training without express permission. | Check eligibility and the retention treatment of each endpoint or feature. Do not assume one setting applies to every API function. |
| Amazon Bedrock or Google Cloud access | Anthropic notes that cloud-hosted access uses the relevant cloud provider’s controls. | Establish which provider’s terms, storage controls, region and administrator access apply to the deployment, as well as Anthropic’s applicable terms. |
| Claude Code and other features | Handling can vary by product surface and feature; the available material does not establish one retention rule for every feature. | Verify the specific feature’s terms and settings rather than relying on assumptions from another Claude product. |
The roles and training-use statements in the table describe Anthropic’s commercial terms as presented in its documentation; they are not a substitute for checking the contract that governs your organisation. Contracts, product settings and feature eligibility can change, so confirm the current version before approval.
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There is no single retention period that applies to every Claude surface and feature. Anthropic’s commercial retention guidance says API inputs and outputs are normally deleted within 30 days. The applicable feature and policy determine whether that standard timeframe applies; saved conversations in Claude products, Files/API features, legal requirements, policy enforcement and feedback can lead to different periods.
Anthropic also documents exceptions for designated Covered Models: prompts and outputs may be retained for 30 days for safety work, with controlled human review in limited cases. Data that is flagged or must be retained by law can be kept longer. ZDR and HIPAA-ready arrangements therefore reduce routine retention for eligible uses; they are not an absolute promise that no information can ever be kept or reviewed.
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Deleting a conversation from chat history is not the same as immediate removal from every backend system or compliance record. Anthropic’s consumer guidance also cautions against assuming that deleting a chat reverses every downstream copy or safety-review pathway. Ask what deletion covers for the specific surface and feature, and how the organisation verifies completion.
Can I paste a work document into Claude?
Only after the use has been approved, the material minimised and the exact commercial configuration verified. Public-chat use should default to no for work documents that contain personal, confidential, regulated or secret information. If the document is genuinely public and contains no restricted details, use only the relevant passage rather than uploading the full file without a reason.
Separate the task from the source document
Write down what you need from the assistant: for example, a summary of a policy clause, a clearer explanation of a process or a draft structure. Then identify the smallest excerpt and fields that can answer that question. Often the assistant can work on a rewritten example or a synthetic scenario rather than the original customer, employee or contract record.
Remove identifiers and unnecessary fields
Redact or pseudonymise names, account numbers, addresses, dates of birth, tokens, URLs containing credentials and unique case identifiers. Replace values with consistent placeholders such as [CUSTOMER_NAME], [ACCOUNT_ID] or [CONTRACT_VALUE]. Keep any mapping needed to restore the original identities in a controlled location outside the assistant.
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Do not treat placeholder substitution as a guarantee of anonymity. A distinctive combination of facts can still identify a person or reveal a confidential matter. Remove details that the task does not require, including information in surrounding text that would make a case recognizable.
Use an approved route and inspect the result
For an approved work use, select the organisation’s designated workspace or integration, not a personal account chosen for convenience. After receiving an answer, check it for exposed identifiers, sensitive inferences and confidential wording before sharing it with anyone else. Human review is part of the handling process, not a formality.
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Approval should cover the actual workflow, not just the vendor’s general privacy page. OAIC recommends due diligence, a privacy-impact assessment, human oversight, transparent policies and ongoing monitoring. Its guidance also warns that AI due diligence is not “set and forget”: fitness for purpose, staff training and monitoring should be reviewed throughout the product lifecycle.
- Define the use. Record the task, the people affected, the categories of information involved and whether the assistant’s output will influence a decision or be shared externally.
- Choose the exact product surface. Identify the account type, workspace, feature, integration and any cloud provider in the data path. Distinguish consumer chat from a work contract or API arrangement.
- Assess privacy and necessity. Determine whether personal information is needed at all, whether a less identifying example would work and what risks remain after minimisation. Complete the organisation’s privacy-impact assessment process where applicable.
- Review contract and technical controls. Confirm controller and processor roles, training-use terms, retention, deletion, subprocessors, region and transfer terms, export rights, administrator visibility, incident obligations and access controls.
- Check feature-level exceptions. If relying on ZDR, HIPAA-ready arrangements or another retention control, confirm eligibility for the customer, feature and endpoint in use. Document safety, legal and feature-specific exceptions.
- Limit access and establish oversight. Use least privilege, strong authentication, approved-use policies and appropriate logging. Train staff on what must not be entered and who reviews the output.
- Monitor and reassess. Review whether the tool remains fit for purpose, whether staff follow the approved process and whether product, contract or organisational conditions have changed.
For Claude for Work, Anthropic describes the organisation as controller and Anthropic as processor, with the organisation controlling membership and able to access or export user-submitted conversation history. Legal, privacy, procurement and security teams should assess what those roles and controls mean for the organisation’s own obligations before approving the service.
What should you compare when choosing an AI assistant?
Do not rank tools by a marketing claim such as “private” or “secure.” Ask for current contractual and technical evidence for each item that matters to the intended workflow. A comparison should distinguish product editions and features rather than treating a vendor as having one uniform data policy.
- Training: Are prompts and outputs used to train models, under what terms, and do those terms differ between consumer and commercial accounts?
- Retention and deletion: What are the default periods, which settings can change them, what features require storage, and how is deletion verified?
- Review and exceptions: Can staff access data for feedback or safety enforcement? What can be retained for legal, policy or safety reasons?
- Hosting and region: Where is data processed or stored, which cloud provider is involved, and what regional-transfer terms apply?
- Organisation control: Who can manage membership, view or export conversations, set retention and respond to user requests?
- Security and accountability: What encryption, key-management, audit-log and incident-response commitments are documented?
- Eligibility: Are ZDR, HIPAA-ready or similar arrangements actually available for the account, feature and use case under consideration?
Where a vendor does not establish a value or commitment for a relevant feature, record it as unknown and resolve it before sending sensitive information. A commitment for one product tier should not be carried over to a consumer account, another endpoint or a cloud-hosted deployment without evidence.
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What is a practical pre-prompt checklist?
Use this short check before submitting text, files or other material to an assistant:
- Have I classified the material and checked the organisation’s policy?
- Does the prompt contain personal details, credentials, payment information, medical information, confidential source text or a unique case identifier?
- Can I complete the task with public material, a synthetic example, a shorter excerpt or placeholders instead?
- Am I using the approved product surface, workspace and feature?
- Do the verified terms and settings cover this data, retention period and use?
- Have I limited access to the people who need it and planned a human review of the output?
If you cannot answer a relevant question, pause and ask the organisation’s privacy, security or legal contact rather than testing the boundary with real data.
Frequently Asked Questions
Can I use an AI assistant to analyze information that is already public?
Usually, public material is a lower-risk starting point than personal or confidential records, but check that your copy contains no private annotations, hidden identifiers or restricted context. Also assess whether the answer could create a new privacy issue by combining details or making an unsupported inference.
What should I do if I accidentally paste sensitive information into an AI chat?
Stop entering related information and follow your organisation’s privacy or security incident process promptly. Record what was sent, when, and through which account, product and feature so the appropriate team can assess exposure; a chat deletion alone should not be treated as proof that every copy has been removed.
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Not necessarily. Unique dates, locations, job details or case facts may still identify someone, and a placeholder can be reversed if its mapping is accessible. Remove unnecessary context and keep any re-identification key outside the assistant under separate access controls.
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