Which AI is the best at Excel?

The Search for a Winner: Why No Single AI Rules Excel

Ask ten blogs which AI is best at Excel and you'll get ten different answers — Microsoft Copilot, Claude for Excel, ChatGPT, Gemini, Shortcut, Paradigm. Each listicle sounds confident. None of them agree. That's not because the writers are careless; it's because there genuinely is no settled winner to point to.

The market is early-stage and fragmented. A practitioner review of AI Excel tools concludes that it's "still very early" and that current tools are "making minimal impact on how analysts actually work in Excel." Even Excel MVP Liam Bastick, writing in FM Magazine, expects the contest to end up fragmented rather than won outright — and Excel itself, with 1.5 billion users and 40 years of history, isn't going anywhere fast.

The deeper problem is trust. Consider what passes for evidence in this space:

• The only accuracy benchmark we found — Shortcut at 77.3% versus Claude for Excel at 66.3% across 20 finance tasks — comes from Shortcut itself, a vendor claim rather than a neutral test.
• One popular comparison ranks GPT for Work first — a product published by the blog's own company.
• Another widely cited review sells its own Excel add-in, a conflict of interest its readers aren't always reminded of.
• A promised 10-tool accuracy test exists only as a teaser page, with no results published.

So when a blog declares a "best AI for Excel," it's usually ranking its own product, repeating a competitor's marketing number, or simply describing features. None of that tells you what will actually work in your workbook.

This article takes a different approach. Instead of a ranking, we offer a neutral, evidence-based breakdown: what each major tool can and can't do, where the real differentiators lie (bulk processing, model choice, platform fit, specialization), and which claims deserve skepticism. Where a number is a vendor claim, we say so. Where independent data doesn't exist, we don't pretend it does.

That skepticism isn't unique to Excel tools. Published research on agent skills found that roughly 26% carry at least one vulnerability, and the same pattern holds: lots of claims, almost no neutral verification. It's exactly the gap SkillzBench is being built to close — an independent directory that benchmarks every skill in a sandbox with the same model, with and without the skill, and publishes the Lift in percentage points, with money never touching scores.

Until neutral Excel benchmarks exist, the honest answer to "which AI is best at Excel?" is: it depends on your workflow — and the rest of this article shows you exactly what it depends on. If you want to go further, agent skills can automate the rest of your spreadsheet workflows; browse and test free ones on SkillzBench. Skills, proven — join the waitlist to see the benchmarks when they're live.

The Contenders: Four Categories of AI Excel Tools

The AI-for-Excel market is still young and fragmented — no tool wins outright, and as Excel MVP Liam Bastick notes in FM Magazine, "which tool ultimately wins may become a fragmented contest." The most useful way to navigate it is by category, because each cluster solves a genuinely different problem.

Native integrations live inside Excel itself. Microsoft Copilot handles formula generation, data cleaning, and trend analysis, and even offered an in-cell =COPILOT() function — but that function is being deprecated from September 14, 2026 in favor of the Copilot side pane. Copilot also requires files saved to OneDrive or SharePoint with AutoSave enabled, and Microsoft's own guidance says it suits "structured, step-by-step tasks" rather than large-scale transformations. Claude for Excel brings a different strength: cell-level citations on every response, so you can trace exactly where each number comes from.

Bulk-processing specialists matter because most AI tools — Copilot, Claude for Excel, ChatGPT, Gemini, and Shortcut included — cannot reliably process thousands of rows at once, per one vendor comparison. The exceptions:

• GPT for Work — claims up to 1,000 rows per minute and 1M rows per run in Excel (note: the comparison ranks its own product first)
• Power BI — the Gartner-rated BI market leader for heavier analytical workloads
• Julius AI — an upload-based option for large datasets

Finance modeling agents target DCF and LBO work specifically. Endex, backed by the OpenAI Startup Fund, automates three-statement models with citation trails for auditability, while Shortcut runs a "plan, execute, verify" multi-agent loop. Shortcut claims 77.3% accuracy versus 66.3% for Claude for Excel across 20 finance tasks — though even the blog citing it flags this as a vendor claim, not a neutral test. That trust gap is exactly what independent benchmarking should close; SkillzBench is being built to test agent skills in a sandbox with the same model, with and without the skill, so lift is measured rather than asserted.

AI-first challengers rethink the spreadsheet rather than bolting AI onto it. Paradigm replaces formula construction with natural-language queries across 5,000+ AI agents, while Quadratic layers SQL, Python, and JavaScript onto a spreadsheet grid with strong version control. Both are compelling but young — their security posture, as FM Magazine notes, "remains to be seen." Platform exclusivity adds one more wrinkle: Copilot and Claude for Excel are Excel-only, Gemini is Sheets-only, and only tools like GPT for Work and Shortcut span both.

Match the Tool to the Workflow, Not the Hype

Ask five analysts which AI is best at Excel and you'll get five different answers — because the honest answer is that the "best" tool depends entirely on what you're actually doing in the spreadsheet. The market is too early-stage and fragmented for a single winner, so the smarter move is to match the tool to the workflow rather than the hype.

Here's how the major tools map to real work, based on a practitioner review of the landscape:

• Finance modeling (DCF/LBO): specialized agents like Endex and Shortcut, which offer citation trails and multi-agent verification loops built for high-stakes finance work
• Ad hoc analysis: ChatGPT, which excels at flexible, quick-turnaround questions
• Multi-sheet workbook generation: Claude Code, better suited to complex multi-file tasks built from specs
• Bulk row-level processing: none of the big names — Copilot, Claude for Excel, ChatGPT, and Gemini all struggle to reliably apply prompts across thousands of rows

That last point deserves emphasis. If your workflow involves cleaning or classifying tens of thousands of rows, the vendor comparison of Excel AI tools found most mainstream assistants simply can't handle it — Copilot is "better suited for structured, step-by-step tasks than large-scale dataset transformations."

Ease of use varies just as widely. Conversational assistants like Copilot and Formula Bot are the easiest entry points, while power tools like KNIME and Shortcut have steeper learning curves but deliver far more automation payoff once configured. Shortcut's automations, in particular, are complex to set up initially — a trade-off worth knowing before you commit.

Pricing needs a reality check too. Microsoft's Copilot runs as a $30/user/month add-on, Claude for Excel requires at least a Claude Pro plan, and usage limits can be consumed quickly. One more trap: marketing pages often advertise models you can't actually select, so verify which models your specific plan offers before choosing.

Finally, treat every benchmark with skepticism. The only accuracy comparison circulating — Shortcut's 77.3% versus Claude for Excel's 66.3% on finance tasks — is explicitly a vendor claim, not a neutral test. That trust gap is exactly why we're building SkillzBench to benchmark AI agent skills in a sandbox with the same model, with and without the skill, publishing the results for free. Until independent testing matures, validate AI output yourself, prefer tools with cell-level citations, and pick based on your workflow — not a vendor's leaderboard.

Validate Before You Trust: Building a Safe AI Spreadsheet Workflow

Every AI spreadsheet tool, no matter how impressive, shares one uncomfortable truth: the output is only as trustworthy as your willingness to check it. Even Microsoft tells users to treat the result as an opening draft rather than a finished report — and Microsoft's own documentation adds that COPILOT function output "should be reviewed and validated for accuracy, especially for critical business decisions."

That warning carries weight coming from the vendor itself. Excel MVP Liam Bastick goes further on data cleaning: "I am not sure I would trust any AI to clean my data without parallel testing elsewhere." His advice, published in FM Magazine, reflects a broader consensus that AI augments analysts rather than replacing them.

One feature worth prioritizing is traceability. Claude for Excel's standout strength, per one comparison, is that every response includes cell-level citations, so you can trace exactly where each number comes from. Similarly, finance agent Endex builds citation trails specifically for auditability in high-stakes environments.

Before trusting any AI spreadsheet output, run it through a basic validation checklist:

• Spot-check AI-cleaned data against the original source, especially for bulk transformations.
• Verify formulas against known results before applying them to live reports.
• Prefer tools that cite the cells or records behind each answer.
• Confirm bulk-processing limits — most tools, including Copilot, cannot reliably process thousands of rows at once.
• Check which AI models are actually available on your plan, not just what marketing pages claim.

Validation also means questioning the benchmarks vendors publish. The only accuracy comparison found in current coverage — Shortcut claiming 77.3% versus Claude for Excel's 66.3% on 20 finance tasks — is explicitly a vendor claim, not a neutral test. And the tool ranked #1 in one popular comparison is the blog's own product. When marketing writes the test, skepticism is the correct default.

That trust gap is exactly what SkillzBench is being built to close. Its benchmarking approach tests every agent skill in a sandbox using the same model, with and without the skill, and publishes the resulting Lift in percentage points separately from any ratings — with money never touching scores. Neutral, reproducible evaluation replaces vendor self-grading.

Once your validation workflow is solid, agent skills can automate the rest of the spreadsheet process. Browse and test free agent skills on SkillzBench to see which ones genuinely lift your results — proven, not promised.