AI makes first drafts cheaper. That makes quality control more important, not less.

Use this short checklist before you ship AI-assisted analytical work.

Logic

• Is the business question stated clearly?
• Is the dataset grain understood?
• Do joins preserve the intended grain?
• Are filters aligned with the requested population?

Numbers

• Do important totals reconcile?
• Are NULLs handled intentionally?
• Do edge cases behave as expected?
• Did the result change in a way you can explain?

Business meaning

• Does the metric mean what the stakeholder thinks it means?
• Were any business rules invented by the model?
• Could someone make a wrong decision from this output?

Documentation

Document the important assumptions, sources, transformations and validation checks. A polished answer without an audit trail is still difficult to trust.

I built my first ebook around this kind of practical AI-assisted discipline.