Spreadsheets store a huge amount of useful business information. The problem is getting answers out of them without spending an hour building pivot tables or wrestling with formulas. Natural language data tools solve exactly this: you ask a question in plain English, the tool figures out the analysis, and you get an answer.
“Which product had the highest margin last quarter?” “Is customer acquisition trending up or down?” “Which sales rep closed the most deals?” These are questions that used to require either Excel fluency or someone to do the analysis for you. Now they take about thirty seconds.
Here’s what the main tools actually do, where they work well, and which one makes sense for how you work.
How These Tools Work
The underlying mechanic is similar across most tools: you describe what you want in plain English, the AI translates that into code or formulas, runs the analysis on your data, and presents the result. You don’t see the code — you just see the answer, usually accompanied by a chart or a plain-English explanation.
Some tools are built into applications you already use (Google Sheets, Excel). Others are standalone tools you bring your data to. The built-in tools are more convenient; the standalone tools are often more capable. Understanding that trade-off helps you pick the right starting point.
| Tool | How it works | Best for | Works with |
|---|---|---|---|
| ChatGPT Advanced Data Analysis | Upload a file, ask questions in chat, ChatGPT runs Python in background | One-off analysis, exploring unfamiliar data, generating charts | CSV, Excel, PDF uploads |
| Julius AI | Connect data sources, ask questions, get charts and explanations | Regular analysis workflows, live data connections, shareable outputs | Google Sheets, CSV, databases, cloud storage |
| Google Sheets Gemini | Built into Google Sheets — ask questions in a sidebar | Users already in Google Workspace who want AI without switching tools | Google Sheets natively |
| Microsoft Copilot for Excel | Built into Excel — summarise, analyse, and generate formulas | Excel power users who want AI assistance without leaving the app | Excel (Microsoft 365 subscription) |
| Rows | Spreadsheet app with built-in AI for analysis and automation | Teams who want AI and spreadsheet in one purpose-built tool | Native app — import from CSV, Google Sheets, databases |
Google Sheets Gemini: The Zero-Friction Option
If your business runs on Google Workspace, the path of least resistance is the Gemini sidebar built into Google Sheets. You open your spreadsheet, open the Gemini panel, and ask questions without leaving the app. It can summarise data, generate formulas, create charts, and answer questions about what’s in the sheet.
The limitation is depth. Gemini in Sheets is good at straightforward questions and formula generation, but for multi-step analysis, statistical questions, or working across multiple sheets, it’s less capable than dedicated tools. It’s the right choice when your questions are simple and you value staying in the tool you already know.
Microsoft Copilot for Excel: Similar Story, Different Ecosystem
Copilot in Excel is the Microsoft equivalent — ask questions in a sidebar, get answers, generate formulas and charts without leaving the spreadsheet. For Excel users, it removes the friction of switching tools and makes AI assistance feel like a natural extension of existing workflows.
Copilot is notably good at formula generation and at explaining what existing formulas do — genuinely useful for anyone who’s inherited a spreadsheet full of complex nested formulas from a predecessor. For analysis, it handles common business questions well but, like Gemini in Sheets, has limits on complexity.
ChatGPT Advanced Data Analysis: The Flexible Option
For one-off analysis or unfamiliar data, ChatGPT’s Advanced Data Analysis is hard to beat. Upload a file, ask what you want to know, and follow up with more questions. It’s particularly good at exploratory analysis — situations where you don’t have a specific question yet and want to understand what the data contains.
The conversation format means you can iterate naturally. “Show me revenue by month” → “now break it down by region” → “which region has the most consistent growth?” — each question builds on the previous one. ChatGPT maintains context through the session and handles these kinds of multi-step explorations well.
The main limitation is that it works from uploaded file snapshots. If your data updates regularly, you have to upload a fresh file each time — which adds friction for regular analysis workflows.
💡 What You Can Actually Ask These Tools
Julius AI: Built for Regular Analysis
If you run similar analyses on a regular basis — weekly sales reports, monthly financial summaries, recurring operational metrics — Julius is worth evaluating. The ability to connect directly to live data sources (rather than uploading snapshots) makes recurring analysis significantly less friction-heavy. Connect once, ask questions whenever your data updates.
Julius also produces cleaner visual outputs than most competitors, which matters if you’re sharing results with people who expect professional-looking charts rather than code-generated graphics. The interface is designed around the data analyst workflow rather than the chatbot workflow, which some users find more natural for data-heavy work.
Rows: The Integrated Option
Rows is a spreadsheet application with AI built in from the ground up rather than bolted on. It has native integrations with data sources, built-in AI analysis capabilities, and a publishing feature that lets you share live spreadsheets as reports. For teams that find themselves constantly exporting data from one tool to create reports in another, Rows collapses that workflow into a single tool.
The trade-off is that it’s a new application to learn rather than AI added to something you already use. For teams whose current spreadsheet workflow is already painful, that learning investment pays back. For teams whose workflow is fine, switching costs are hard to justify.
Privacy and Data Handling
Every tool in this list processes your data on external servers when you upload or connect files. For most business data — sales reports, marketing metrics, operational numbers — that’s a non-issue. For data containing customer personal information, sensitive financial records, or anything subject to confidentiality obligations, review the provider’s data handling terms before connecting a live data source. Most tools have enterprise tiers with stronger data privacy commitments for organisations where this matters.
One practical step: before connecting a live database to any of these tools, ask whether you can use anonymised or aggregated test data for initial evaluation. You’ll get a clear picture of the tool’s capabilities without exposing production data during the trial period.
Which One Should You Start With?
Key Takeaway
What This Means for Small Businesses
The tools covered in this article have lowered the barrier to data access significantly. A business owner who knows what question they want answered can now get that answer in minutes, without needing to hire a data analyst, learn SQL, or pay for enterprise BI software. The technology isn’t perfect — it makes mistakes, and you should sanity-check important outputs — but it’s good enough to be genuinely useful for most of the data questions that come up in day-to-day business decisions.
The limiting factor is no longer the tools. It’s knowing what to ask. Spend more time thinking about the specific question that would help you make a better decision, and less time worrying about which tool to use to answer it. Start with the tool you already have access to, and upgrade from there only if it genuinely can’t answer your questions.
The Shift Worth Making
That’s a meaningful shift for small businesses especially — where the person who understands the data is often also the person making the decisions, and where paying for a dedicated data analyst isn’t realistic. The right tool, used consistently, gives that person direct access to the answers they need.
The practical answer depends on where you already work. Already in Google Workspace? Try Gemini in Sheets first — it’s the fastest path to your first useful AI data answer. Already paying for ChatGPT Plus? Use Advanced Data Analysis before adding another tool. On Microsoft 365? Copilot in Excel is your natural starting point.
The combination of better tools and lower barriers means that in 2026, the main limit on data access in small businesses isn’t technical anymore — it’s knowing what question to ask. The tools handle the rest.