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The checklist below separates personal use from workplace responsibilities and gives you a repeatable way to judge a chatbot, a prompt and the answer it produces.
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1. Decide whether the task belongs in a chatbot
Define the outcome before opening the tool
Write down what you want the system to do: brainstorm names, summarize text, explain a concept, transform code, draft a message or help organize information. A precise purpose makes it easier to decide what data is necessary and what could go wrong.
Then ask what happens if the answer is wrong. A mistaken spelling suggestion is inconvenient; an incorrect medication instruction, legal interpretation, payment instruction or security command can cause real harm. The higher the consequence, the less suitable an unreviewed chatbot answer becomes.
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Apply the context test
NIST’s AI Risk Management Framework 1.0 (2023) says, “It is the joint responsibility of all AI actors to determine whether AI technology is an appropriate or necessary tool for a given context or purpose, and how to use it responsibly.” That means there is no universal safe-use setting. The same chatbot may be reasonable for generating interview questions but inappropriate for deciding whether a person qualifies for a benefit.
- Low consequence: Use the output as a draft or starting point, then perform a quick plausibility check.
- Moderate consequence: Check factual claims against authoritative material and have another person review the result before acting.
- High consequence: Treat the chatbot only as an aid. A qualified human must make or approve the decision.
2. Keep sensitive information out unless the use is approved
Data that should not be pasted casually
Do not enter information that could enable account takeover, identity theft, discrimination, extortion, confidentiality breaches or commercial damage. Examples include:
- Passwords, recovery phrases, authentication codes, API keys and private encryption keys.
- Bank, payment-card, tax, government-identification and other financial-account details.
- Private medical records, therapy notes, genetic information or insurance identifiers.
- Personal addresses, telephone numbers, precise location histories and identity documents.
- Confidential client communications, unpublished research, source code, trade secrets and internal incident reports.
- Classified, export-controlled or otherwise restricted material.
A chatbot may request a secret while appearing helpful. Never disclose it merely because the prompt asks. If the task genuinely requires protected data, stop and use the organization’s approved process rather than guessing that a consumer account is suitable.
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Remove names, account numbers, dates of birth and other identifiers before asking for help. Replace them with neutral labels such as Customer A or Project X. Generalize dates, locations and amounts when the exact value is not needed. Check the remaining text for embedded metadata, tracked links, screenshots and hidden comments; redaction is incomplete if the original information can still be reconstructed easily.
Do not assume that replacing a name makes a record anonymous. A combination of job title, unusual event, location and date may identify a person. If the context remains sensitive, do not upload it.
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Personal accounts and workplace accounts are different
The Australian Cyber Security Centre (ACSC) gives the direct instruction: “Do not enter sensitive or classified information into AI tools unless that has been approved.” For work, approval should come from the organization’s security, privacy or data owner, not from an individual’s informal judgment. Follow the organization’s approved-tool list, classification rules, contractual restrictions and incident-reporting procedure.
An employer may approve one deployment or account tier while prohibiting an apparently similar public service. Approval can depend on where data is stored, who can administer the account, whether retention can be controlled and whether a contract limits secondary use.
3. Read the service’s current data practices
Questions to answer before the first prompt
Privacy notices, terms and account settings change. Review the documentation for the exact product, region, account type and plan you will use. Look for clear answers to these questions:
- What information is collected from prompts, uploaded files, feedback, device telemetry and account activity?
- How long are conversations and files stored, and where are they processed?
- Can prompts or outputs be used to improve, evaluate or train models? Is that use optional, mandatory or different for business accounts?
- Who can access content for operations, abuse investigation, support or legal compliance?
- Can administrators, shared-workspace members or connected applications see conversations?
- What history, export, correction and deletion controls exist, and what do those controls not remove from backups or legal records?
- Does the service disclose subcontractors, international transfers and contractual handling of customer data?
Record the date you checked the policy and the settings you selected when the information is important. Provider-specific claims should never be generalized to every chatbot: the Australian Cyber Security Centre’s guidance explicitly notes that collection, storage, retraining use and contractual handling vary by service and product tier.
Check settings, not just marketing language
Open the privacy or data-control panel and inspect conversation history, model-improvement choices, link sharing, file retention, personalization and connected-app permissions. A setting that prevents future use for improvement may not delete conversations already stored. A deleted chat may also remain in an organization’s retention system or a legal hold. If the interface does not explain a control clearly, treat the behavior as uncertain and keep sensitive material out.
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Do not confuse a bounded prototype with a consumer guarantee
NIST Interagency Report 8579, an initial public draft dated 31 July 2025, describes risks and mitigations considered for a specific internal-use chatbot, including prompt injection, hallucinations, data exposure and unauthorized access. It mentions local deployment, access controls and validation filters, but expressly is not implementation guidance. Its controls are an example of system design, not evidence that a public chatbot provides the same protections.
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Secure the account
- Use a unique, strong password and multi-factor authentication where available.
- Review active sessions, recovery methods and administrator accounts.
- Do not share credentials or leave a sensitive conversation open on a shared device.
- Understand whether conversation links, exports or shared projects can be viewed by anyone who receives a link.
Limit permissions and connectors
Some chatbot tools can read cloud drives, mailboxes, code repositories, calendars or business systems. Connect only the source required for the task, grant the narrowest available permission and remove access when it is no longer needed. Broad access turns a harmless question into a potential data-exposure path if the account is compromised or an instruction is manipulated.
For workplace use, confirm that the connector, plug-in or automation is approved. Keep personal and company accounts separate so a work document is not accidentally processed under a personal history or billing profile.
Keep an audit trail for consequential work
Save the source documents, the final human-approved result and the date of review. Do not rely on a chatbot transcript as the sole record of a decision: conversation history can be edited, deleted or unavailable to colleagues who need to reproduce the work.
5. Recognize and resist prompt injection
What prompt injection means
Prompt injection is input manipulation intended to hijack an AI system’s behavior or bypass safeguards. The malicious instruction may be in a user message, a web page, a document, an email, an image or retrieved search content. It can tell the model to ignore previous instructions, reveal hidden text, send data elsewhere or claim that a safety restriction has been removed.
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The danger is not limited to obviously hostile wording. A document can contain an instruction that looks like ordinary content, and a fluent chatbot may follow it while presenting the result as legitimate.
Safe handling steps
- Separate data from instructions. Treat uploaded material as untrusted content to analyze, not as authority over your account or workflow.
- Ignore requests for secrets. A document or chatbot should never obtain passwords, tokens or private keys simply because it asks.
- Pause on unexpected actions. Do not authorize an email, purchase, file deletion, code execution or external transfer without checking the exact target and data involved.
- Verify claims outside the model. If the output says that a policy was bypassed, a citation is official or a restriction does not apply, confirm it in the original system.
- Reduce tool access. Disable connectors and automation while analyzing untrusted content when those capabilities are not necessary.
Review documents safely
Ask the chatbot to identify instructions contained in a document instead of following them. Read the original yourself, especially if the document requests disclosure, payment, privilege escalation or a change to security controls. Treat an answer that claims to have used a tool or checked a source as unverified until you can see the actual result.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.6. Check every answer before using it
Fluency is not evidence
Generated text can be confident, coherent and wrong. The ACSC recommends, “Check AI-generated results carefully before using them.” Check names, dates, calculations, quotations, citations, code behavior and statements of policy against reliable primary sources. When a citation is provided, open it and confirm that it actually supports the claim; a plausible-looking reference may be incomplete or misrepresented.
Match the check to the claim
| Output type | Minimum check before use |
|---|---|
| Summary or rewrite | Compare it with the original for omitted qualifications, changed numbers and invented details. |
| Calculation or spreadsheet formula | Recalculate independently with a trusted tool and inspect units, assumptions and rounding. |
| Legal, medical, tax or financial explanation | Check current official guidance and obtain advice from a suitably qualified professional. |
| Security or system command | Test in an isolated environment, inspect the command’s effects and obtain approval before production use. |
| Quotation, statistic or historical claim | Locate the original publication and confirm the wording, date, scope and context. |
| Code or configuration | Review dependencies and permissions, run tests and examine failure and rollback behavior. |
Watch for missing uncertainty
Ask what assumptions the answer made and which facts would change the conclusion. A useful follow-up is: “List the parts you are least certain about and the primary sources I should check.” This does not make the answer reliable by itself; it helps you target the human verification that remains necessary.
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7. Require qualified human judgment for high-stakes decisions
NIST describes trustworthiness as contextual and includes validity and reliability, safety, security and resilience, accountability and transparency, explainability and interpretability, privacy and fairness. An answer can be useful in one dimension and unacceptable in another.
Health
Do not use a chatbot alone to diagnose symptoms, choose treatment, calculate a dose or decide whether urgent care is needed. Use it, at most, to prepare questions or organize information for a licensed clinician, and verify any medical statement with that clinician or an authoritative health service.
Legal and financial matters
Do not rely on generated text alone for a contract, filing, eligibility decision, investment, debt action or tax position. Laws and rules depend on jurisdiction, dates and individual facts. A qualified professional must review the relevant source and your circumstances.
Employment, education and access decisions
Do not let an unreviewed output determine hiring, discipline, grading, benefits, housing, insurance or access to services. Check for missing context, discriminatory assumptions and an explanation that can be defended to the affected person.
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Safety and security
For physical safety, cybersecurity, industrial control or emergency response, use approved procedures and accountable personnel. NIST notes that intervention may be needed when an AI system cannot detect or correct its own errors.
8. Use a simple workflow for everyday tasks
- State the task and consequence. Write what you need and what could happen if the result is wrong.
- Choose an approved service. For work, confirm the organization, account tier and connector are permitted.
- Minimize the input. Remove secrets, identifiers and unnecessary confidential context.
- Inspect the data controls. Check collection, retention, model-improvement use, access and deletion settings for that service.
- Prompt for a bounded result. Specify the format, assumptions and source material; do not grant authority to take external action.
- Scan for manipulation. Treat uploaded or retrieved instructions as untrusted and ignore requests for secrets or policy bypasses.
- Verify the output. Check primary sources, calculations, quotations and operational effects.
- Obtain human approval. Escalate whenever the consequence is high or the answer is uncertain.
- Record the decision. Preserve the approved result and the sources used, according to your organization’s retention rules.
9. What to do after a mistake or possible exposure
If you entered a secret
Stop using the exposed credential, revoke or rotate it through the authoritative system, and report the incident according to the account owner’s procedure. Do not paste the replacement secret into the chatbot to test whether it works.
If confidential information was uploaded
Record what was shared, when, under which account and with which recipients or connectors. Use the service’s deletion controls if appropriate, but do not assume deletion eliminates backups or legal records. Notify the organization’s privacy or security contact so it can assess contractual, regulatory and customer-notification duties.
If an answer caused harm or may be wrong
Stop further distribution, preserve the original output and inputs, identify decisions affected by it and notify the accountable human owner. Correct the result using authoritative sources rather than asking the same chatbot to certify its own answer.
10. Keep the checklist current
The ACSC page was published and last reviewed on 24 January 2024, while NIST says its AI RMF 1.0 and Playbook are being updated. Dates and controls therefore matter: a safe decision today should be revisited when the service or its rules change.
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