How to check AI-generated calculations and tables
Checking calculations produced by AI takes more than asking the same model whether it is certain. You need to identify the rule, reproduce the arithmetic and compare the result with the input data.
We will review a fictional productivity table. The method works for numerical summaries in reports, spreadsheets and presentations, even when the answer’s wording looks perfectly organized.
1. Separate the claim from the calculation
Turn each conclusion into a question you can verify. “The team improved” is broad; “the total increased from 80 to 100” allows an objective comparison.
Record the original values, period and unit. If one number represents interactions and another represents people, the operation may be wrong before you reach the arithmetic.
| Fictional measure | Before | After |
|---|---|---|
| Completed interactions | 80 | 100 |
| Hours worked | 40 | 50 |
| Interactions per hour | 2 | 2 |
The total increased, but hourly productivity stayed the same. This example shows why checking the sum alone does not validate the interpretation.
2. Reproduce the calculation elsewhere
Growth from 80 to 100 is (100 − 80) ÷ 80, or 25%. Use a calculator or spreadsheet to verify the result with those same values.
If the AI claims productivity increased, also compare 80 ÷ 40 and 100 ÷ 50. The appropriate conclusion depends on the metric you defined, not the most persuasive sentence.
Microsoft’s documentation on Excel formulas provides a reference for checking how an expression is assembled in that application.
3. Check denominators and filters
For percentages, always identify the denominator. Dividing by the starting value answers a different question from dividing by the final value.
For averages, check which records entered the calculation and whether values are missing. A simple average of percentages from differently sized groups may not represent the combined result.
Request each group’s totals before combining their rates. If those data are unavailable, record the limitation instead of accepting a number reconstructed through assumptions.
4. Request a checking report
Use AI to organize the review stages. It can help identify inconsistencies, while your independent calculation remains the reference.
Review the table without changing the original data.
List each numerical claim, its formula and its input values.
Distinguish growth in the total from productivity per hour.
Flag missing data and conclusions that do not follow from the table.
Do not invent values to complete a calculation.Compare that report with what you reproduced. If the results differ, return to the rule and input data before asking for another draft of the explanation.
5. Test rounding and presentation
Keep sufficient precision during calculation and round the displayed result according to its purpose. Adding values that have already been rounded can differ from calculating the total with greater precision.
Also check whether charts use the same period and baseline as the table. An incorrect label can change the interpretation even when individual numbers are correct.
Write the chosen rounding policy beside the table. That makes small display differences easier to explain to someone reviewing the document later.
6. Keep an auditable record
Save the data, formula, filters and reviewed result. This lets you repeat the analysis when the dataset changes instead of relying on text that has lost its context.
To prepare a clearer input before reviewing, read how to organize a CSV for AI.
Frequently asked questions
Is asking AI to check its own answer enough?
No. Reproduce the calculation in a calculator or spreadsheet using the same data, then compare both the rule and result.
How does growth in a total differ from productivity?
A total measures output volume. A productivity measure relates that output to a resource, such as hours worked, and may stay unchanged while total output grows.
What should I keep to repeat an analysis?
Keep the dataset, formulas, filters, rounding policy and reviewed result.