Copy-paste formulas to run AI across rows in Google Sheets
Paste a formula into row 2, test it on a few rows, then drag down to run the workflow across your spreadsheet.
Summarize a row
A: long text · B: what to extract
=GPT("Summarize this text for the goal that follows. Text: " & A2 & ". Goal: " & B2 & ". Return 2-3 concise sentences and note anything missing.")
Classify / label
A: text · B: allowed labels
=GPT("Classify this text into exactly one of these labels: " & B2 & ". Text: " & A2 & ". Return the label and a one-line reason. If unclear, return Needs review.")
Enrich / research a company
A: company or domain · B: source notes · C: what you want
=GPT("Research this company: " & A2 & ". Source notes: " & B2 & ". What we want: " & C2 & ". Return a concise summary, useful signals, missing data, and one next action. Treat unsourced facts as estimates.")
QA an AI output
A: AI output · B: source text · C: required fields
=GPT("QA this output: " & A2 & ". Source text: " & B2 & ". Required fields: " & C2 & ". Return missing data, risky assumptions, unsupported claims, and pass/review/fail.")
What people mean by “Claude for Sheets”
Many people search for “Claude for Sheets,” “Claude in Google Sheets,” or a “Claude for Sheets extension” because they want one thing: run an AI model across the rows of a spreadsheet instead of copying cells into a chat window one at a time. That intent is about the workflow, AI applied to every row, not just one specific model.
GPT for Sheets is built for exactly that workflow. It adds AI formulas to Google Sheets so you can summarize, classify, enrich, and research across an entire table, with the inputs and outputs side by side for review.
“Claude” and “Anthropic” are trademarks of Anthropic. GPT for Sheets is an independent product and is not affiliated with, endorsed by, or sponsored by Anthropic. Model and provider availability is configured through your own API keys; check the product documentation for the current list of supported models before relying on any specific one.
Fastest path: Install GPT for Sheets → add an input column → connect your API key → paste a formula → review 10 rows → fill down.
How GPT for Sheets runs AI across rows
A practical AI-in-Sheets table usually has these columns:
| Column | What to put there | Why it matters |
|---|---|---|
| A | Input text, company, domain, or row record | Stable row anchor for each prompt |
| B | Source notes, snippet, or context | Keeps the AI grounded in inspectable evidence |
| C | Instruction, label set, or goal | Makes the output specific |
| D | AI output (summary, label, enrichment) | The result you fill down |
| E | QA flag | Prevents unsupported claims from moving forward |
Step-by-step setup
- Install GPT for Sheets and connect your model/provider API key.
- Start with 10 representative rows before filling down hundreds or thousands.
- Keep raw source fields unchanged so you can audit the AI.
- Add constraints: max length, output format, allowed labels, and what to do when data is missing.
- Add a QA formula that flags missing facts and unsupported assumptions.
- Fill down once the prompt works on sample rows.
Choosing a model for your task
Different tasks suit different models. Short classification and labeling jobs can use a faster, cheaper model; longer research and summarization may benefit from a more capable one. Because models are configured through your own provider keys, you can pick what fits your budget and quality needs and test a few rows before running the whole sheet. Verify the current list of supported models in the documentation rather than assuming any one model is available.
Use cases
- Lead enrichment: turn a list of companies or domains into researched, reviewable rows.
- Research: summarize long text, pages, or notes into structured fields.
- Classification: label tickets, reviews, or leads into consistent categories.
- Data cleanup: normalize messy exports into consistent fields for CRM, ads, or reporting.
- QA: flag missing evidence and rows that need human review.
Best for / not best for
Best for: people who searched for AI in Google Sheets and want to run prompts across many rows for enrichment, research, and classification without copy-paste.
Not best for: users who require one specific named model exclusively, or who need a fully managed proprietary dataset rather than a spreadsheet-native AI layer.
Internal links and next workflows
- GPT for Sheets product page
- GPT for Sheets get started
- Set up AI provider keys
- GPT for Sheets vs Claude for Sheets
- AI lead enrichment in Google Sheets guide
- Upgrade GPT for Sheets
Safety, compliance, and data quality
AI output should be treated as a draft. Keep source columns visible, store source URLs or dates when relevant, and review important rows before outreach, publishing, or decisions. Do not infer sensitive attributes. Provider and model availability depends on your own API keys and the current product documentation.
Frequently Asked Questions
Is GPT for Sheets the same as Claude for Sheets?
No. GPT for Sheets is an independent product, not affiliated with Anthropic, and “Claude” is a trademark of Anthropic. GPT for Sheets gives you the same core workflow people want, running AI across spreadsheet rows for enrichment, research, and classification.
Which models can I use?
Models and providers are configured through your own API keys. Check the GPT for Sheets documentation for the current list of supported models, since availability can change.
Do I need to copy and paste between a chatbot and Google Sheets?
No. GPT for Sheets lets you run AI formulas directly in cells, which is better for bulk prompts, repeatable QA columns, and reviewed exports.
Should I trust every AI output automatically?
No. Treat output as a structured draft and use QA columns to flag missing evidence, unsupported claims, and rows that need manual research.
Start running AI in Google Sheets
If you came looking for AI in your spreadsheet, install GPT for Sheets and run these formulas where your data already lives.
Install GPT for Sheets or compare plans to turn rows into reviewed research, labels, enrichment, and next actions.