Responsible AI at Work.

How to use AI in your job without getting fired, sued, or creating a PR disaster.

After this lesson you'll know

How to create or follow a workplace AI policy
The 5 questions to ask before using AI for any work task
How to bring AI into your team responsibly
What to do when there's no policy yet

The Reality

Most companies don't have an AI policy. Yet.

Studies show that the majority of employees are already using AI at work — but most companies haven't established formal policies around it. This creates a gray zone where well-meaning people can accidentally violate client confidentiality, create legal liability, or undermine trust.

Whether your company has a policy or not, you need your own framework for responsible AI use at work.

The Checklist

5 questions before using AI for any work task.

Does this involve confidential data?

Client info, trade secrets, employee data, financials? If yes, anonymize or don't paste it.

Will someone rely on this being accurate?

If the output will inform decisions, go into reports, or be sent to clients — verify every factual claim.

Should I disclose that AI was used?

Consider your audience, your company's expectations, and whether the context demands transparency.

Could this output be biased or harmful?

Hiring criteria, performance reviews, customer-facing content — check for bias before publishing.

Am I adding enough human judgment?

AI should augment your thinking, not replace it. If you're copy-pasting without reading, you're doing it wrong.

For Teams

Bringing AI into your team responsibly.

If you're a manager or team lead, here's how to introduce AI without chaos:

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Start with guidelines, not bans. Blanket bans just drive AI use underground. Clear guidelines make it safe and visible.

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Define approved tools. Which AI tools can your team use? Free accounts? Paid? Company-licensed?

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Set data boundaries. What can and can't go into AI tools? Make this extremely specific.

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Require human review. All AI output that goes to clients or gets published should be reviewed by a person.

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Train, don't just regulate. Teach your team HOW to use AI well. Rules without skills lead to frustration.

Policies

What a good workplace AI policy actually looks like.

If you're in a position to create or influence your company's AI policy, here's what the best ones include. If you're following a policy, this helps you understand why each element matters.

Approved Tools List

Name the specific AI tools employees can use and at what tier (free, pro, enterprise). Specify which tools have data protection agreements with the company and which don't. Update quarterly as the landscape changes.

Data Classification Rules

Categorize data into tiers: public (can share freely with AI), internal (can share with approved enterprise tools), confidential (must anonymize first), restricted (never share with any AI tool). Give concrete examples for each tier.

Output Review Requirements

Define what needs human review before publishing or sending. At minimum: anything client-facing, anything with factual claims, anything involving hiring or performance evaluation, and anything published under the company name.

Disclosure Standards

Specify when employees must disclose AI use, how to disclose it, and approved disclosure language. Different departments may need different standards — marketing, legal, and engineering face different contexts.

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