Workplace rules
What to do when your workplace has no clear AI policy.
If the message is "use AI" but the boundaries are vague, your hesitation is not weakness. It is a signal to create safer questions before you paste, trust, or send.
Why this matters
Policy gaps create personal anxiety.
When training and rules lag behind adoption, workers are left to guess what is safe. That guesswork creates avoidable risk and makes normal AI learning feel loaded.
The five questions to answer before using AI at work.
Which tools are approved?
Do not assume a personal AI account is acceptable for work content.
What data is off limits?
Clarify customer, employee, financial, confidential, unreleased, and private information.
What needs human review?
Know which outputs need manager, legal, HR, finance, safety, or policy review.
What use is encouraged?
Find low-risk examples your team actually supports.
Where do questions go?
Identify the person, channel, or document that settles uncertainty.
Copy-paste prompt: ask for AI boundaries without sounding difficult.
Safe default while you wait for clarity.
Do
- Use public or invented examples.
- Remove sensitive details.
- Check outputs before sharing.
Ask
- Which tool is approved?
- What data is allowed?
- Who reviews risky outputs?
Avoid
- Personal accounts for private work.
- Customer or employee data.
- Policy assumptions.
A same-day operating boundary.
Draft with generic context.
Use AI for structure, wording, questions, and checklists before you add real workplace details yourself.
Keep risky content outside the tool.
Do not paste customer, employee, financial, legal, confidential, or unreleased material unless your workplace has clearly approved that use.
Name the reviewer.
If the output affects people, money, customers, compliance, safety, or reputation, decide who reviews it before it is used.