How to Use AI to Clean and Analyze Spreadsheets

Spreadsheet work used to require knowing the right formula or building a pivot table by hand. AI has changed this for most analysis tasks. Microsoft Copilot in Excel and Google Sheets' Gemini can take natural language requests like 'show me revenue by region with year-over-year growth' and produce the analysis. ChatGPT with code interpreter and Claude with code execution can take a CSV upload and do almost anything — clean messy data, find duplicates, calculate statistics, detect outliers, generate visualizations, and explain what they found. The non-technical user workflow: drop your file into the AI, describe the question you actually want answered ('which products are losing money this quarter?'), and let it produce the analysis with charts and explanation. For ongoing work, Anthropic's Claude in Excel integration and Microsoft's Copilot let AI live inside the spreadsheet, available for any cell or range. Specialized tools push further. Rows and Bricks build spreadsheets where AI is a first-class citizen, able to fetch data from APIs, analyze it, and present it without manual ETL. For data cleaning specifically, AI excels at fuzzy matching (consolidating 'NY', 'New York', 'N.Y.' into a single category), date format normalization, and identifying suspicious values that don't fit patterns. The skills that still matter for the human: knowing what question to ask, validating the AI's analysis (especially for high-stakes decisions), and understanding which methods are appropriate for your data. AI handles the mechanical work of analysis; you handle the judgment about what the analysis means.