Checking AI output, protecting data and knowing when not to use AI
How to catch hallucinations and errors, what data never to paste into an AI tool, and which decisions must stay with people.
Using AI at work responsibly means treating its output as a draft from a fast but unreliable assistant. You remain responsible for anything you send, publish or decide.
Why checking is necessary
AI chat assistants generate text that sounds right. That is different from being right. Common problems include:
- Hallucinated facts: dates, figures or names that are invented.
- Fake references: report titles or links that do not exist.
- Calculation errors: wrong totals, percentages or formulas that run but give wrong results.
- Out-of-date information: rules or prices that have changed.
- Biased wording: phrases that exclude groups, such as age-related terms in a job advert.
A practical review routine
- Check every number and name against an original source you can read yourself.
- Test formulas and code on examples where you already know the answer.
- Read the output as the recipient would. Is the tone right? Does it promise anything you cannot deliver?
- Remove anything you cannot verify rather than leaving it in.
Asking the assistant "Are you sure?" is not verification. It may confidently agree with itself.
Protecting data
Text you paste into a public tool may be stored or used outside your control. Unless your company has approved a tool for that data, do not paste:
- Customer personal details such as names, phone numbers, addresses or ID numbers.
- Passwords, API keys or access codes.
- Confidential pay, contract or financial information.
- Unreleased plans or internal documents.
When you need help with sensitive material, replace real details with placeholders, for example [Customer A] and [amount], and follow your employer's AI policy.
When not to use AI
Some decisions should stay with qualified people: medical advice to a patient, legal advice on a specific contract, financial approvals, and hiring or disciplinary decisions about individuals. AI can help prepare notes for these, but a person must review the facts and make the call. It is also a poor choice when you cannot check the answer at all.
Habit to build: before using AI output, ask two questions. What here could be wrong, and how would I know?
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