Using AI at work is no longer unusual. What is easy to miss are the risks hidden behind the convenience: confidential material leaving the building, a model error landing in a report, a licensing problem in published material. Most of these incidents are preventable with a short list of rules.
These seven apply regardless of which tool your company uses.
1. Start with your employer policy
Before anything else, find out whether your organization has an AI usage policy. A growing number specify approved tools, prohibited data types and required review steps.
If no policy exists, at minimum agree with your manager on what you plan to use it for. After an incident, there was no rule is not a defense.
2. Keep confidential material out
Pasting customer lists, unreleased results, or contract terms into a consumer AI service means transmitting company information to an outside server.
If you need a summary or review, replace names, company names and figures with placeholders first. If your employer provides a contracted business tier that excludes your data from training, use that instead as a matter of course.
3. Treat every output as a draft
Models are wrong in a confident voice, which is precisely what makes the failure mode dangerous. Verify every figure, quotation and regulatory interpretation against a primary source before it reaches a document with your name on it.
Accountability sits with whoever submits the work. The AI told me so has never been an acceptable explanation.
4. Check licensing before publishing
Before using generated images or copy in customer-facing material, confirm the service terms permit commercial use. Terms differ between providers, and some restrict commercial rights to paid tiers.
Output that imitates a specific living artist style or depicts a real person raises separate legal and ethical issues. For business use, avoid it.
5. Be more careful where people are affected
Screening job applications, evaluating performance, or classifying customers deserves extra caution. Models reproduce bias present in training data, and this is an area of active regulatory tightening in many jurisdictions.
Do not begin these use cases on individual initiative. They warrant an organizational review.
6. Leave a record
When AI contributed materially to a deliverable, note which tool did what. One line is enough. It makes problems traceable and turns individual discoveries into shared team knowledge.
7. Do not let it replace your fundamentals
AI makes capable people faster. It does not supply judgment. Handing over work you could not evaluate yourself is not delegation — it is abdication.
This matters most early in a role or in an unfamiliar domain. Attempt the work first, then use AI to review it. That order compounds in your favor over a career.
The rule in one line
Inside company policy, without sensitive data, verified by me.
Hold to that and AI becomes the most useful tool on your desk. Pick one task today and apply it.
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