Excel Copilot Analyst in 2026: Let AI Write and Run Python Code to Analyze Your Data

If your job still involves stitching together five regional spreadsheets by hand before a Monday meeting, 2026 is the year to stop. The Analyst agent inside Microsoft 365 Copilot for Excel has quietly become one of the most useful tools on the ribbon, and most office workers still don't know it exists. It doesn't just answer questions about your data — it reasons through a problem step by step, writes real Python code, runs it, and shows you exactly how it got its answer.

What Is the Analyst Agent in Excel Copilot?

The Analyst agent reached general availability in mid-2025 and has since become a core part of the Copilot experience in Excel for anyone with a Microsoft 365 Copilot license. Under the hood, it's built on a reasoning model that works through chain-of-thought steps rather than guessing at an answer in one shot. When you ask it a question, it plans an approach, writes Python to execute that plan, checks the output, and adjusts if something looks off.

The April 2026 update pushed this further by making Copilot's agentic capabilities generally available and by adding Python directly inside “Edit with Copilot” in Excel. That means you can now ask Copilot to transform data, build visualizations, and complete multi-step cleanup tasks in place, without ever leaving the workbook or opening a separate Python environment.

What Makes Analyst Different From Regular Copilot Chat

Regular Copilot chat in Excel is great for quick formula help or explaining what a cell does. Analyst is built for a different kind of problem: messy, multi-file, multi-step analysis where the path to the answer isn't obvious. Two things set it apart.

Multi-file reasoning — Analyst can work across more than one file at a time, which makes it well-suited to consolidating regional reports, reconciling versions, or merging exports from different systems.

Visible reasoning — instead of a black-box answer, you see the steps Copilot took and the actual Python code it ran, so you can sanity-check the logic before trusting the output.

How to Use the Analyst Agent Step by Step

Step 1: Open the Copilot Pane and Select Analyst

In Excel, open the Copilot pane and choose the Analyst agent (sometimes surfaced as “advanced data analysis” in the agent picker). This works on workbooks stored in OneDrive or SharePoint, since Copilot needs access to the underlying file to reason over it.

Step 2: Describe Your Question in Plain Language

Be specific about the outcome you want, not the mechanics. Something like “compare Q2 revenue across all three regional tabs and flag any region where growth fell more than 10% below plan” gives Analyst enough structure to build a real plan of attack.

Step 3: Review the Reasoning Steps and Generated Code

Analyst will show its thinking as it works: what it checked first, what it found, and the Python it used to get there. Skim this before accepting results, especially for anything that will end up in a report someone else will rely on.

Step 4: Ask Follow-Ups and Refine

Treat the first answer as a draft. You can ask Analyst to re-run the analysis with a different assumption, break results out by month instead of quarter, or export the cleaned data as a new table — all in the same conversation.

Real-World Use Cases

Reconciling sales figures scattered across regional workbooks into one clean summary table — a task that used to mean an hour of copy-pasting and manual VLOOKUPs.

Spotting anomalies or outliers in expense data that would take an analyst hours to eyeball manually, including flagging duplicate reimbursements or out-of-pattern charges.

Building a quick forecast model from historical data without writing a single formula, then asking Analyst to explain which assumptions drove the projection.

Cleaning inconsistent date formats, currency symbols, or duplicate entries before a report goes out, with a clear before-and-after summary of what changed.

Merging exports from different systems — a CRM export and a finance export, for example — into a single reconciled view without manual mapping.

Common Mistakes to Avoid

The most common misstep is treating Analyst's first answer as final. Because it's genuinely capable of handling ambiguous requests, it's easy to forget that “ambiguous” still means it had to make judgment calls somewhere along the way. Always skim the reasoning trail for the specific assumption that matters most to your use case — how it handled missing values, how it defined a “region,” or which date range it assumed you meant.

A second mistake is pointing Analyst at files it doesn't actually have access to, or at a workbook still saved only locally rather than in OneDrive or SharePoint. Since Analyst needs to open and reason over the underlying file, save your workbook to the cloud first if you want multi-file analysis to work reliably.

A Licensing Note

Analyst requires a paid Microsoft 365 Copilot seat. Following the April 15, 2026 changes to free Copilot Chat access in Office apps, agentic features like Analyst are firmly on the premium side of the line — something worth checking with your IT admin if you're not sure which tier your account has.

Quick FAQ

Does Analyst work on files stored only on my local drive?

Reliably, no. Analyst performs best — and multi-file reasoning specifically requires — workbooks saved to OneDrive or SharePoint, since that's how Copilot accesses the underlying data.

Can I see the actual Python code Analyst wrote?

Yes. Part of what makes Analyst different from a typical chatbot is that it shows its reasoning steps and the code it generated and executed, rather than just handing you a final number.

Is Analyst the same as Python in Excel?

They're related but distinct. Python in Excel lets you write and run your own Python directly in a cell; Analyst is an agent that writes and runs Python on your behalf as part of a guided, multi-step analysis, with the April 2026 update bringing Python directly into the Edit with Copilot experience as well.

Get Started Today

The best way to understand Analyst is to throw a genuinely messy dataset at it — the kind you'd normally dread opening on a Friday afternoon. Start small, read the reasoning steps it shows you, and build trust from there. Once you see it correctly reconcile three inconsistent spreadsheets in under a minute, it's hard to go back to doing it by hand.