The quality of a generated answer is not the same as the quality of its evidence.
Understand the idea
Generative AI can help summarize, draft and brainstorm, but it can also produce plausible errors, omit context or fabricate supporting references. NIST’s Generative AI Profile treats false confident outputs as a risk that organizations should manage. For workplace use, accountability remains with the people and processes approving the output.
How to apply it
- Clarify whether the task is low-risk brainstorming or a decision that affects people, safety, finance, compliance or customers.
- Follow company policy; do not put confidential, personal or restricted information into an unapproved tool.
- Separate factual claims, numbers, citations and conclusions from stylistic wording.
- Trace key claims to current primary sources, original documents or reproducible calculations.
- Ask a knowledgeable human to review sensitive or high-impact outputs and record any remaining uncertainty.
- Edit the output for context, fairness and the audience; use it only after approval where required.
Workplace example
A project coordinator asks AI to summarize a monthly progress report. The text is polished, but one percentage is wrong and one root cause is invented. By checking the source tables and review notes, the coordinator corrects both before distributing the update.
What to watch out for
Verification should be proportionate to consequence. A creative headline does not need the same controls as an engineering calculation or legal interpretation. Do not rely on AI as the final authority in regulated or safety-critical work.
Try it in the next seven days
For the next AI-assisted draft, create a small fact-check table with claim, original source, reviewer and decision.