Classify the input
Identify personal, confidential, regulated, contractual, client, employee, and proprietary material before you paste anything. Use the strictest applicable company rule.
Safe AI at work
How to use AI safely at work
A practical checklist for handling confidential information, sources, factual review, and human responsibility when using AI at work.
The short answer
Use the least sensitive context that can do the job, follow employer policy, name sources, verify consequential claims, and keep a responsible human in the approval path. When the policy is unclear, stop and ask the system owner.
Use this guide when you need to
- Decide what information is safe to share with an AI tool.
- Review an AI output for factual and source risk.
- Use company knowledge without hiding where claims came from.
- Set a human approval point for consequential work.
The method
A repeatable way to do the work
Start with a small, real task. Keep the source material and review path visible.
Minimize the context
Replace names with roles, remove identifiers, summarize sensitive passages, and include only the details needed for the task. More context is not automatically better context.
Require source visibility
Ask the model to distinguish provided facts, cited material, assumptions, and suggestions. For research, open the original source and verify the claim there.
Match review to consequence
Low-risk drafts need a quick human check. Legal, financial, personnel, safety, client, or public claims need the qualified review your organization normally requires.
Start here
Field notes for the work moment
Each note gives you a small move, an example, and an artifact you can keep.
Keep naming sources
Preserve attribution inside company knowledge workflows.
Read the Shift →The two jobs you cannot hand to AI
Keep responsibility and judgment with people.
Read the Shift →The mistake that sounds right
Catch plausible output before it travels.
Read the Shift →Ask what it is missing
Expose uncertainty and missing inputs.
Read the Shift →Before you call it a win
Review the evidence against the original goal.
Read the Shift →AI between two jobs
Keep responsibility clear across a handoff.
Read the Shift →AI is becoming part of the job
Adopt tools without removing accountable review.
Read the Shift →The appreciating asset
Preserve the knowledge that makes future work safer.
Read the Shift →You are not behind
Choose useful adoption over anxiety and speed.
Read the Shift →Common questions
What to know before you start
What information should I never paste into a public AI tool?
Do not paste material prohibited by policy or contract, including credentials, private personal data, protected client information, trade secrets, or regulated records. Tool and organization rules differ.
How do I verify an AI citation?
Open the original source, confirm it exists, read the relevant passage, check the date and context, and make sure the source supports the exact claim.
When is human review mandatory?
Use human review whenever the output could materially affect people, money, rights, safety, compliance, clients, or the public. Follow the existing approval chain for that work.
Editorial note: This page organizes original ThinkShift field notes. It was reviewed on 2026-09-02. Changing product, policy, legal, or security claims require current primary sources and qualified review. See our editorial standards.
One useful shift at a time
Get the next practical AI work move.
Two or three short issues each week. Every issue names a real work moment and leaves you with something you can use.