Spreadsheets are where a lot of real work happens, and they are also where a lot of people get stuck: a formula that will not behave, a column of inconsistent dates, a data set that needs a summary by Friday. AI assistants have become genuinely useful here, whether through built-in features such as Copilot in Excel and Gemini in Google Sheets or by working with a general assistant.
Updated September 2026: we added links to Microsoft’s and Google’s documentation for their spreadsheet AI features and to OpenAI’s guidance on checking AI data analysis.
1. Get formulas written and explained
Describe what you want in plain language and include your column layout:
Example prompt Column A has order dates, column B has customer names and column C has order totals. Write a formula for cell F2 that sums the totals for the customer named in E2, but only for orders in 2026. I am using Excel.
Always say which program you use, because Excel and Google Sheets functions differ in places. If you inherit a spreadsheet full of nested formulas, paste one in and ask the assistant to explain it step by step.
2. Clean messy data
AI is good at describing how to standardize data, and at writing the formulas or scripts to do it:
- Split full names into first and last names
- Standardize date formats and phone numbers
- Remove duplicates while keeping the most recent record
- Categorize free-text entries, such as expense descriptions, into set categories
For large or sensitive data, ask for the method or formula and apply it yourself, rather than pasting thousands of rows into a chat.
3. Analyze and summarize
Many assistants can analyze an uploaded spreadsheet by writing and running code behind the scenes. This is far more reliable than a model doing arithmetic in its head. ChatGPT, for example, writes and runs Python code for this kind of analysis, and OpenAI advises users to "review the generated code, outputs, and assumptions before relying on the result." Useful requests include:
- “What are the three biggest changes between Q1 and Q2?”
- “Which products account for 80 percent of revenue?”
- “Show monthly totals as a line chart.”
- “Are there any unusual values I should double-check?”
4. Build templates and trackers
Ask for a structure: “Design a simple budget tracker with categories, monthly columns, totals and a variance column.” You get a starting layout you can refine.
How to avoid silent errors
Spreadsheet mistakes are dangerous because they look authoritative. Build these checks into your routine:
- Test formulas on rows you can verify by hand.
- Check ranges, since a formula that stops at row 500 when your data goes to 520 will quietly undercount.
- Confirm totals against a known figure, such as last month’s report.
- Ask the assistant to show its work, including the code it ran for any analysis.
- Watch for assumptions, like how blanks, text values or duplicates were treated.
Rule of thumb If a number from an AI analysis will go in front of your boss, a client or an auditor, recompute it independently or trace it to the source cells first.
Privacy
Spreadsheets often contain customer names, salaries and financial data. Use your organization’s approved AI tools for work files, and remove personal information when you only need help with structure. Our privacy guide has more detail.
From an afternoon to a conversation
AI turns spreadsheet problems that used to require an expert, or an afternoon of searching forums, into a short conversation. Let it write and explain formulas, clean data and draft analysis, then apply your own judgment to check that the numbers are right.
Sources
- Get started with Copilot in Excel, Microsoft Support
- Collaborate with Gemini in Google Sheets, Google Docs Editors Help
- Data analysis with ChatGPT, OpenAI Help Center
