An AI-generated spreadsheet formula can return a plausible number while answering the wrong question. It might use the wrong date field, omit the final rows, divide by the wrong total, or interpret a blank as zero. A tidy workbook and a confident explanation do not reveal those mistakes automatically.
AI can still be a useful formula assistant when the task is defined clearly and the result is checked independently. This guide shows a practical review process for everyday operational spreadsheets, using a worked example that calculates elapsed time between two timestamps.
Start with a plain-language calculation rule
Before asking for a formula, describe the inputs, output, units, and exceptions. “Calculate response time” leaves too much open. “Calculate elapsed calendar minutes from the request timestamp in column A to the first response timestamp in column B” defines a more useful task.
Decide what should happen when either value is missing, the response predates the request, or the timestamp is stored as text. Also decide whether nights and weekends count. Calendar minutes and business hours require different logic; the assistant should not choose between them silently.
Write these decisions in a notes sheet or adjacent documentation. Someone reviewing the workbook later needs the rule as well as the formula. If the business changes its definition of response time, that is a calculation change worth recording.
Prepare a small, safe sample
Work in a copy of the workbook and preserve the original. Give the assistant column names, data types, spreadsheet version, and several invented rows that represent the real structure. Sensitive customer records are usually unnecessary for designing a time-difference formula.
Microsoft’s Copilot in Excel FAQ warns that generated formulas and explanations can be inaccurate and should be reviewed and verified. Treat that as a practical design constraint: build the check before applying the suggestion to thousands of rows.
Keep the sample representative. If production data contains missing values, duplicated identifiers, or dates in different formats, include those conditions. A perfectly clean five-row example can hide the problems the real workbook needs to handle.
Calculate expected results independently
Create a small set of test cases whose answers you can calculate without the proposed formula. These become a reference for checking both the output and the assumptions. Use actual date-and-time values, not text that merely looks like a timestamp.
- October 7 at 09:00 to October 7 at 10:30 should give 90 elapsed minutes.
- October 7 at 23:30 to October 8 at 00:15 should give 45 minutes.
- Identical valid timestamps should give zero minutes.
- A missing response should follow your explicit missing-data rule.
- A response before the request should be flagged for investigation.
The overnight case is particularly useful. If the input stores only times without dates, the sheet does not contain enough information to distinguish the next morning from an earlier time on the same day. Fix the data model or define the assumption explicitly.
Keep the simple core visible
For two valid Excel date-time values in the same time zone, =(B2-A2)*1440 converts the difference in days into minutes. This example does not handle missing, reversed, or text inputs; those checks need a deliberate surrounding rule. Working through the simple core helps you evaluate a longer AI-generated formula.
Ask for an explanation and a change list
A focused prompt could request a formula, a plain-language explanation of each part, the required input types, and how every sample case should behave. Name the Excel version so the assistant does not assume functions your team cannot use.
If the tool can edit the workbook directly, limit the request to a defined output range and ask it to list changes. Review those changes before saving the shared version. A successful formula does not justify unrelated edits to source data, existing totals, or sheet structure.
Use the explanation to identify assumptions, but do not treat it as independent verification. The same assistant can repeat the same mistaken interpretation in both the formula and its explanation. Compare the actual cell results with your manually determined examples.
Inspect references and data types
Open the formula and trace where its inputs come from. Confirm that the request and response columns are correct, the range includes the intended rows, and fixed references remain fixed when the formula is copied. Check at least the first, middle, and last populated rows.
Inspect dates and numeric values that were imported from other systems. A date may be stored as text, and a number may contain a hidden space or use an unexpected decimal separator. Resolve the import convention instead of wrapping every problem in an error-suppression function.
Microsoft’s formula error guidance describes tools for investigating errors, but a formula can be logically wrong without displaying an error. A total over the wrong range may calculate perfectly. Use the workbook’s auditing tools alongside the expected-result checks.
Check exceptions and summaries together
Decide how invalid rows should appear in downstream reports. If missing responses become zero minutes, an average response-time figure may look artificially low. If invalid rows disappear entirely, the report may hide the fact that requests remain unanswered.
Keep a separate count of valid, missing, and flagged records. For example, a summary can show an average for completed valid responses alongside the number still waiting. Explain the denominator and the period covered so readers understand what the average describes.
Avoid converting every formula error into a blank. A blank can be an intentional display choice, but it can also conceal a broken lookup or malformed input. Keep the diagnostic signal available to the person maintaining the workbook.
Recheck when new data arrives
Append several representative rows and confirm that formulas, totals, charts, and filters include them. Check what happens when a source column is renamed or reordered. A workbook that works on today’s export can fail quietly when next month’s file changes shape.
Maintain the field definitions used during data migration and mapping. The definition of each timestamp or identifier should remain clear across the source system and the spreadsheet.
Release a reviewed version with an owner
Record the calculation rule, sample checks, reviewer, and date in the workbook documentation. Store the approved version where colleagues can identify it, following a consistent shared-file routine. Explain any changed output to people using the report.
For consequential calculations, have someone with the relevant domain knowledge review the assumptions as well as the formulas. AI assistance can reduce the time spent drafting spreadsheet logic, while clear specifications and independent checks determine whether that logic is suitable for the work.
Featured image: original AI-generated editorial illustration for CCM Marketer.