The spreadsheet is where most knowledge work actually happens, and 2026 is the year the AI vendors finally stopped treating it like an afterthought. Anthropic put Claude directly inside Excel — out of beta and generally available for Microsoft 365 as of May. Microsoft now lets you swap Claude in for GPT inside Copilot’s Agent mode. Google shipped a Gemini in Sheets that claims a 70% success rate on autonomously editing real, messy workbooks. And the upload-based tools like Julius and ChatGPT’s Data Analyst kept getting sharper.
So if you live in spreadsheets — building financial models, cleaning exports, auditing someone else’s tab of horrors — which one do you reach for? I’ve been running the same kinds of tasks through all of them. The short version: they’re not interchangeable, and the right pick depends heavily on whether you care most about formula correctness, staying inside your existing files, or just getting an answer out of a data dump.
What actually changed in 2026
Three shifts matter here.
First, Claude moved into the Office apps natively. Anthropic launched Claude for Microsoft 365 to general availability in May 2026, with Excel, Word, and PowerPoint fully released and Outlook still in beta. Inside Excel it can read specific cells, change an assumption inside an existing formula without snapping the rest of the model, and build a workbook from a blank sheet. The interesting bit, which Anthropic doesn’t market loudly, is that it runs sub-agents that pass context between files — so a conversation can carry from your spreadsheet into the deck you’re building off it.
Second, Microsoft opened up the engine. You can now choose Anthropic’s Claude alongside OpenAI’s models inside Microsoft 365 Copilot, including the Researcher agent and Agent mode in Excel. That’s a real change in posture — for two years Copilot meant OpenAI under the hood, full stop.
Third, Google caught up on the Sheets side. The Gemini in Sheets relaunch in spring 2026 can build and edit complex spreadsheets from plain language, pull context from your other Workspace files, and turn unstructured notes into clean tables. Google quotes a 70.48% autonomous success rate on real-world sheet manipulation, which is a telling number — it means roughly one in three complex tasks still needs a human to step in.
The contenders, briefly
- Claude in Excel — a native add-in (and now a Copilot model option) focused on formula integrity and workbook reasoning.
- Microsoft 365 Copilot — built into Excel, Word, the lot; deepest integration with your tenant and data.
- ChatGPT (Data Analyst) — upload a file, get analysis and charts via a Python sandbox. Not living in your spreadsheet.
- Julius — a dedicated AI data analyst that chats with your files and connects to live databases.
- Gemini in Sheets — native to Google Sheets, strong on natural-language building and Workspace context.
- Formula Bot and friends — lightweight tools for one-off formula generation, fine for quick jobs, out of their depth on real modeling.
Formula accuracy: the thing that actually breaks trust
This is where the gap is widest, and it’s the one most roundups skip because it’s annoying to test.
A formula that’s 90% right is worse than no formula, because you ship it, the number looks plausible, and you find out three weeks later the nested IF collapsed an edge case. So the bar isn’t “can it write a SUMIFS” — every tool can. The bar is deeply nested logic, array operations, error handling, and not silently breaking adjacent cells.
Claude in Excel has been the most reliable here in my testing, and I think there’s a structural reason. Because it edits inside the live workbook and can read the surrounding cells, it adjusts an assumption without rewriting the whole formula chain — the exact failure mode that makes you distrust AI in a model. When you change a growth rate in a forecast, you want that one input touched, not a “helpful” refactor of twelve dependent cells.
Copilot in Excel is competent and getting better, especially now that you can route it through Claude. Its advantage is that it sees your actual data and named ranges, so its formulas reference the right things more often. Its weakness has been verbosity and occasional over-confidence on complex array logic.
ChatGPT’s Data Analyst is excellent at analysis but it’s solving a different problem. It runs Python on an uploaded copy of your data, so what you get back is the answer and a chart — not a clean formula sitting in your sheet. If you want the working spreadsheet, that’s a mismatch.
Gemini in Sheets is strong on building from scratch and decent on standard formulas, but that 70% figure is honest about the ceiling. For routine work it’s quick; for gnarly logic I still verify everything.
Data cleaning and transformation
Messy real-world sheets — inconsistent dates, merged cells, half-empty columns, three different spellings of the same vendor — are where the upload-based tools shine and the native ones sometimes stumble.
ChatGPT and Julius both handle this well because they run actual code against the data. Dedup, reshape wide-to-long, parse a free-text column into structured fields — that’s a Python job, and they do it cleanly. Julius edges ahead for repeat work because it remembers your data context across a session and connects to live databases on its Pro plan, so you’re not re-uploading a CSV every time.
Gemini’s “turn messy notes into a table” feature is genuinely good for the common case of pasting in unstructured text. Smart Fill has also gotten noticeably faster at inferring intent.
Claude and Copilot can clean data too, but inside the constraints of the spreadsheet’s own tools, which is more limited than a code sandbox for the truly ugly stuff. The trade-off is that the result lives in your file with no export-reimport dance.
Reasoning over a whole workbook
Here’s an underrated use case: you inherit a 14-tab model someone built and left, and you need to understand what it does and find the broken reference that’s throwing #REF.
Claude in Excel is the standout for this, and it’s the clearest argument for a native, context-carrying agent. It can explain what a sheet does, trace dependencies, and flag the cell that’s poisoning your totals — because it can actually see the structure, not a flattened upload. The cross-file sub-agent behavior helps when the model spans workbooks.
Copilot does a respectable version of this within your tenant. The upload tools are weaker here, because reconstructing a multi-tab model’s logic from a flat export loses exactly the structure you’re asking about.
A concrete example from last month: I handed each tool a 9-tab budget model with a circular reference nobody could find. Claude in Excel traced it to a self-referencing cell on the consolidation tab in one pass and explained the loop in plain language. Copilot got close but flagged the wrong tab first. The upload tools couldn’t see the inter-tab links at all once the workbook was flattened to CSV, so they were effectively guessing. That’s the whole case for native agents in one anecdote — structure is the information, and uploading throws it away.
Where the lightweight tools fit
Don’t dismiss the single-purpose tools entirely. Formula Bot and similar generators are genuinely faster for the “I just need one REGEX-heavy formula and I’ll paste it myself” job. They’re not trying to reason over your workbook, and for a quick one-off that’s a feature, not a limitation. Where they fall apart is anything stateful — multi-step cleaning, model audits, or work that depends on the rest of your sheet. Use them as a calculator, not an analyst, and you won’t be disappointed.
Integration and privacy: what leaves your tenant
This one’s easy to overlook and then regret.
Native agents — Claude in Excel, Copilot, Gemini in Sheets — work inside your existing environment. For Copilot and Gemini that means your data stays in your Microsoft or Google tenant under your existing data-handling terms, which is the answer most enterprises need. Claude as a Copilot model option inherits Microsoft’s data boundary; the standalone Claude add-in routes through Anthropic, so check your org’s policy.
Upload-based tools (ChatGPT, Julius) mean your data goes to their service. For public or low-sensitivity data that’s a non-issue. For anything with PII, financials, or anything under contract, it’s a conversation with your security team before you paste a single row. Don’t assume — verify the data-handling terms for your specific plan.
What it costs
Pricing is genuinely confusing right now because everything is mid-promotion. As of June 2026:
- Microsoft 365 Copilot — the Business add-on is around $18/user/month on a promo running through June 30, 2026, rising to $21/user/month after. Enterprise sits at $21/user/month on annual commitment (down permanently from the old $30), with month-to-month around $25.20. It requires an eligible base Microsoft 365 license on top.
- Claude Pro — $20/month, which now includes the Excel add-in. If you’re routing Claude through Copilot instead, you’re paying the Copilot license, not this.
- ChatGPT Plus — $20/month; Team runs higher per seat. Data Analyst is included.
- Julius — free tier at 15 messages/month; Plus at ~$29/month annual (uploads only); Pro at ~$37/month annual (no message cap, live database connectors); Max at ~$166/month; Business seats at $450/month for three editors.
- Gemini in Sheets — now bundled into Google Workspace subscriptions, with promotional higher limits through July 15, 2026, before per-user caps kick in.
The honest read: if you already pay for Microsoft 365 or Google Workspace, the native AI is the cheapest incremental option because you’re partly already paying for it. Standalone tools like Julius justify their cost only if you’re doing serious, repeated data analysis that the bundled options can’t match. Confirm the current numbers before you buy — these are moving monthly.
So which one should you actually use?
For finance and FP&A modelers — people who live and die by formula correctness and inherited models — Claude in Excel is my pick. The formula integrity and workbook reasoning are the differentiators, and a wrong number in a model is expensive. Route it through Copilot if your org needs the Microsoft data boundary.
For data analysts doing exploratory work on messy exports, Julius or ChatGPT’s Data Analyst win. The code sandbox handles cleaning and transformation that the native tools can’t match, and you mostly want the answer, not a permanent formula. Julius if it’s recurring and database-connected; ChatGPT if it’s ad hoc.
For Google Workspace shops and casual users, Gemini in Sheets is the sensible default — it’s already bundled, it builds quickly from natural language, and for everyday tasks the 70% ceiling is fine as long as you sanity-check the complex stuff.
For anyone already paying for Microsoft 365 who wants one tool across Excel, Word, and Outlook, Copilot is the path of least resistance — and now that you can put Claude behind it, you get a lot of Claude’s formula strength inside Microsoft’s data boundary.
The meta-point: none of these is good enough to trust blind. The 70% number Google published is the most useful disclosure any vendor made this year, because it’s the real one — roughly a third of hard tasks still need you. Pick the tool that fits where your data lives and what you’re optimizing for, then check its work like you’d check a junior analyst’s. Try running the same broken formula through two of them this week and see which one actually finds the bug.
Sources: The New Stack — Claude across Office, Claude for Microsoft 365 general availability, Microsoft 365 Copilot 2026 pricing, Julius AI pricing 2026 (Coefficient), Build and edit complex spreadsheets with Gemini in Sheets.