An Inside Look at Copilot in Excel
When you ask Copilot in Excel to “add a drop-down menu to this column” or “fix this formula in the team inventory tracker,” behind the scenes, Copilot reasons about your intent, picks and applies the right Excel features, and then edits the workbook. This can feel straight forward for some tasks but, now imagine you’re a Finance professional asking Copilot in Excel: “What’s broken in this valuation model, and how does fixing it change the outcome?” This is not a simple single formula request; it is an end-to-end finance workflow. To tackle it, Copilot needs to inspect the workbook, understand the finance specific business question, identify assumptions and formulas that may be wrong, correct the model, recalculate outputs, and explain the impact in a way a finance professional can trust. A good answer is not just “here is the new result.” A good answer is a clear, auditable explanation of what changed, why it changed, and its impact on values in the model. That kind of prompt is what we think of as an L4 workflow: an open-ended business problem that requires multiple steps, multiple Excel capabilities, and domain judgment. It is also a great way to understand why evals matter. To provide a great response to this question, many different operations and features need to ladder together successfully to deliver the final result. So how do we make sure every part comes together to solve the customer's intent? This is the job of our evaluation system, aka our "evals.” We’ll provide a brief tour through how we think about evals in Excel: what they are, how we organize them, the benchmarks they produce, and how we use these results to make Copilot in Excel better every week. What are evals, and why do we have them? An eval is a repeatable test of Copilot quality. We give Copilot in Excel a task and a starting workbook, let it do its work, and then grade the output against a series of checks and rubrics. These checks go beyond just confirming whether a value is correct. They also assess whether the workbook is usable, auditable, well- formatted, and aligns to Excel best practices. We evaluate more than the final workbook output. For agentic workflows, the path to the result matters too: what steps the agent took, which tools it called, how many turns it needed, how long the experience took end to end, and more. Looking at that trajectory helps give us a clearer measurement of whether the agent is becoming more accurate, capable, and efficient at how it reaches the desired result. Evals measure Copilot quality and are how we move from “this feels better” to “this is measurably better.” A prompt tweak, model upgrade, or a new tool can improve one customer intents while quietly making another worse. Our evals help us catch those regressions before they reach customers, as well as quantify improvements from new capabilities and find quality gaps early enough to prioritize fixes. How we organize our evals Excel is used by millions to complete a wide range of work: tracking lists, analyzing sales, managing operations, building financial models, planning budgets, and much more. Even the same task can have different expected answers whether you’re a finance professional or a small business owner. To measure Copilot in Excel quality reliably, we ensure our eval cases represent the breadth of customer workflows and all the different flavors of spreadsheets they use. We organize eval cases across several dimensions. Complexity is one of the most important dimensions, because it lets us test the building blocks separately while also testing the full customer workflow. We also categorize cases by customer role, domain, workbook characteristics, Excel feature usage, and more, so our benchmarks reflect the breadth and depth of real Excel work. Complexity: L1 through L4 We think about task complexity as a ladder. At the bottom are atomic actions and individual features. Higher up are multi-step tasks. At the top are open-ended workflows that sound more like business problems. The important point is that an L4 workflow is only as strong as the L1, L2, and L3 capabilities underneath it. L4 workflows: solving an open-ended business problem, such as debugging a valuation model or determining how much cash is available for debt service. L3 multi-step tasks: combining features to complete a defined goal, such as creating a sales summary worksheet or building a cash-flow bridge. L2 feature usage: using an Excel capability correctly, such as creating a PivotTable, applying conditional formatting, building a chart, or using formula auditing. L1 actions: single operations such as inserting a row, editing a formula, formatting a cell, or creating a label. Let’s go back to the valuation example at the start of the blog: “What’s broken in this valuation model, and how does fixing it change the outcome?” Copilot needs to break the work into several major steps: inspect the model structure, locate the key assumptions, audit the formulas, correct the calculation logic, compare the before-and-after outputs, and summarize the business impact. Each step sounds simple at the surface, but each depends on many smaller capabilities working reliably. Level What it means How it shows up in the valuation scenario L4: Workflow Solving an end-to-end business problem “What’s broken in this valuation model, and how does fixing it change the outcome?” L3: Multi-step task Composing multiple Excel capabilities to reach a goal Identify incorrect assumptions Correct formulas Recalculate outputs Quantify the impact L2: Feature usage Using one Excel capability correctly Apply formula auditing Update cross-sheet references Build comparison tables Document changes L1: Action Performing a single atomic operation on the grid Edit a formula Insert a table Format cells, values Write a label and notes Check cell reference Customer role and vertical domain What a good workbook looks like in Excel is often domain-specific. A formula that is acceptable in a general spreadsheet may not meet the bar for a finance model. A summary that works for a small business owner may not be enough for a consultant preparing a client deliverable for a large enterprise. That is why we build and review eval cases with domain-specific expectations in mind. We’ve worked closely with industry partners and customers to validate coverage, review input and output workbooks, and author grading rubrics and success criteria. Through these processes, we ensure our evals are realistic, aligned to expert human judgement, and reflect their taste and domain specific expertise. For example, we look at the shape of the workbook itself: number of sheets, workbook size, data density, formulas, tables, charts, and other Excel features. Real workbooks are rarely tidy single-tab examples. They can be large, messy, and full of context. Another example is our finance-specific rubrics for model structure, formula construction, auditability, and presentation quality. From categories to benchmarks Once we have categorized our eval cases, we curate them into benchmarks. Our goal here isn’t a single benchmark or a single number. Rather, we have different benchmarks for the different types of decisions we face while building Copilot in Excel. Some of our benchmarks provide broad coverage with an emphasis on comparability. Others target Excel-specific behaviors and customer workflows for specific feature areas or customer segments. Here is a subset of the benchmarks we use internally: Public benchmarks One public benchmark used by many spreadsheet products is SpreadsheetBench, a benchmark of spreadsheet tasks that provides broad coverage of common operations. Internally, we’ve further curated and validated subsets of this benchmark to adjust ambiguous queries, improve grader correctness, and improve signal to make results more easily applicable. However, we believe our internal benchmarks better reflect the type of work and expectations of Excel customers. Private benchmarks In addition to public benchmarks we maintain several internal benchmarks within the Excel team. Some examples include: RegressionBench helps us detect whether a change has broken something that used to work. CustomerBench focuses on matching production customer distributions across task complexity, domains, workbook shapes, and other dimensions. This provides an signal that mirrors customer usage. OfficeJSBench measures whether the operations Copilot generates to act on the workbook execute reliably and produce the intended result. FinanceBench is one of our deep and challenging vertical benchmarks focused on finance workflows and uses finance-specific rubrics for correctness, structure, and auditability. We developed FinanceBench with input and review from partners like Financial Modeling Institute (FMI), Microsoft Finance, and other finance professionals and customers. The collection of these benchmarks provides both broad and granular measurements on quality. They allow us to measure where the agent is strong, where it can improve, and whether a change has the intended impact on the customer experience. How eval results make Copilot in Excel better Evals are not just a reporting mechanism - they are deeply integrated into how we build the AI experience in Excel. Eval benchmarks help: Gate releases: Benchmark runs are part of how we decide whether a feature is ready to advance from our validation environments to customer availability. If evals detect issues or the improvement doesn’t show intend impact, the change does not move forward. Improve based on customer signals: When a customer conversation or signal reveals opportunity for improvement, we classify it and then create representative eval cases for it. We can then fix it and measure improvement in subsequent eval runs. Model training: We use rubrics and graders from evals to provide signal to tune models for spreadsheet work. Inform the right model for the job: Comparable benchmark results help us route tasks to models that balance quality, latency, and capability, to provide the best experience to customers. Over time, this creates a virtuous cycle: feedback and usage identify opportunities, evals quantify them, fixes and training address them, benchmarks confirm the win, and the next release starts from a higher bar. Why the hero scenario matters Coming back to the valuation prompt, the reason it matters is that it represents the kind of work people increasingly want Copilot in Excel to help with. They do not just want help inserting a chart or writing one formula. They want help completing meaningful work: understanding a model, finding an issue, improving the analysis, and making the result easier to trust. We can only deliver that L4 experience if the underlying layers are strong. Formula edits have to be correct, feature usage has to be reliable, multi-step plans have to stay coherent, and the final workbook has to be clear, complete, and auditable. That is why our eval system measures both the broad set of things people do in Excel and the deep workflows that matter most in demanding domains like finance.New in Excel for the web: The full Power Query experience
We’ve reached yet another milestone in Excel for the web: The full Power Query user experience is now generally available, including the import wizard and Power Query Editor. After we released the ability to refresh Power Query data from authenticated data sources, we were able to unlock the ability to complete the full user journey of importing data and editing it using Power Query. Getting started Learn all about Power Query in Excel for the web here > See this support article for more information on Power Query data sources in Excel versions. Note: Viewing and refreshing queries is available to all Microsoft 365 Subscribers. The full Power Query experience is available to all Microsoft 365 Subscribers with Business or Enterprise plans. Importing data You can import data into Excel using Power Query from a wide variety of data sources, for example: Excel Workbook, Text/CSV, XML, JSON, SQL Server Database, SharePoint Online List, OData, Blank Table, and Blank Query. Select Data > Get Data: In the Choose data source dialog box, select one of the available data sources: Connect to the data source. After you select the source, the authentication kind will be auto-populated, according to the relevant source (you can still change it, if you like). Press Next, and choose the table you wish to import: Press Transform data to open the table in the Power Query editor, where you can perform many powerful transformations. Note: You can open the editor whenever you need it, by using Data > Get Data > Launch Power Query Editor. When you are done, load the table – press Close & Load to load to the Excel grid: Or Close & Load to - to either load to the Excel grid, or create a connection-only query: See the query was created in the Queries & Connections pane: If you loaded to a table, you can see it on the Excel grid: You can refresh the created query from the Queries & Connections pane, or by using Data > Refresh/Refresh All. You can also perform operations, such as editing the query (with the Power Query Editor), renaming it, and more: What’s next? Future plans include adding data sources and advanced features. Feedback We hope you like this new addition to Excel and we’d love to hear what you think about it! Let us know by using the Feedback button in the top right corner in Excel - add #PowerQuery in your feedback so that we can find it easily. Want to know more about Excel for the web? See What's new in Excel for the web and subscribe to our Excel Blog to get the latest updates. Stay connected with us and other Excel fans around the world – join our Excel Community and follow us on Twitter. Jonathan Kahati, Gal Horowitz ~ Excel Team
New ways to customize how Copilot edits your workbooks
If you’ve ever typed the same formatting and style instructions into your Copilot prompt every single time - don’t merge cells,” “use my header style,” “name the tables this way”- we built two new features for you! These new customization options let you set your rules once and have Copilot follow them automatically. Personalization is now generally available, and workbook rules are rolling out to general availability across Excel for Web, Windows, and Mac. Personalization: your rules that follow you Personalization lets you tell Copilot your standing preferences once, and it follows them across every workbook you touch. No more repeating yourself. Copilot learns your preferences before it starts editing, so the output always reflects the guidance you provide. Set preferences for things like: Formatting: “Never merge cells.” “Don’t use red in charts.” “Always format currency in USD with no decimals.” Naming conventions: “Name tables with a tbl prefix.” “Use clear, descriptive sheet names.” Formulas: “Write formulas with structured table references, not cell ranges.” PivotTables & report styles: “Default to my standard summary layout with bold headers and subtotals.” How to access it Open Copilot in Excel. Open Settings (...) → Personalization. Add your preferences in natural language and save. Copilot applies them every time you prompt it. Workbook rules: standards that follow the workbook Where Personalization is about you, workbook rules are about a specific workbook. Rules live in the workbook and travel with it when you share it, so teams and organizations can standardize how a file should look and behave, and everyone who uses Copilot to edit it stays consistent. These rules are stored in the workbook as a sheet with the “.Rules” naming convention, which signals to Copilot that they should be followed for all edits made in the workbook, regardless of the user. What makes workbook rules especially powerful is the ability to tap into Excel’s calculation engine, giving you a low-barrier way to leverage the Excel functionality you already know how to use. Unique ways to leverage workbook rules: Point to an exact example: Format a sample range exactly how you want it, then tell Copilot “match this formatting”—an exact example beats a written description. Make rules dynamic with formulas: Reference cells, ranges, or other sheets so rules can change based on what’s already in the workbook. For example, applying one instruction when a project is over budget and another when it is on track. Use Copilot to build and edit the rules sheet: Start from a blank .Rules sheet or an existing template, then ask Copilot to draft, refine, or update the rules. Aim it at an existing, well-built example sheet and ask it to infer the rules automatically for a fast way to standardize an established template. Share for consistency: Because the rules are stored in the workbook, every collaborator and every future version stays on-standard. Share rules sheets with others to bring into their own workbooks for consistency. How to access it Open Copilot in Excel. Open + → Create workbook rules. This creates a new template. Add rules in plain language, point to an example range, or ask Copilot to generate rules from a sample sheet. Rules must be in column A of the sheet, but can reference other areas of the sheet (e.g. example of a formatted table of range). Note: If you have an existing sheet you'd like to leverage, simply rename the sheet with ".Rules" and start adding your rules in column A. Try it today: Personalization is available to all Copilot in Excel users on Excel for Web, Windows, and Mac. Learn more about Copilot in Excel personalization. Workbook rules is available in the Insiders channel for Windows and Mac and rolling out to general availability in the coming weeks. Learn more about Copilot in Excel workbook rules.Introducing federated Copilot connectors for LSEG and Moody's in Excel
Earlier this month, we announced Microsoft 365 Copilot federated connectors were coming to Copilot in Excel. Built on the emerging industry standard Model Context Protocol (MCP), federated connectors pull data into Microsoft 365 Copilot live at query time, helping bring institutional data sources into the tools customers already use every day. Starting today, Copilot can now pull the latest data from LSEG and Moody’s directly into your Excel workbook. This is the first set of trusted data providers we’re bringing into Excel, with more on the way. For many finance teams, the work starts before the analysis even begins: finding the right market data, copying values into a model, and making sure nothing got lost along the way. With federated connectors in Excel, Copilot helps bring that information into the workbook where the real work is already happening. Because these connectors query source systems at the moment a request is made, responses reflect the latest available data, helping with scenarios such as checking a deal’s current status or a company’s stock rating. That means less time stitching together inputs and more time analyzing, modeling, and making decisions with the most current data. How it works In Copilot, open the Sources menu, connect to LSEG or Moody’s with your provider credentials, and turn the source toggle on. From there, when you specify a data provider in the prompt or your request references specific data sources such as credit ratings or spot rates, Copilot will retrieve the relevant data and ask you to confirm the data source before incorporating it into responses or results inserted into the sheet. LSEG The LSEG connector brings institutional market data — including foreign exchange rates, equities, and pricing — straight into Excel. This makes LSEG data and services available through a standardized, AI-ready interface and enables both users and agents to access trusted LSEG context inside the workflows they already use, while preserving governance, entitlements and control. For a treasury team updating a hedging model or preparing a leadership readout, that means less exporting, less manual copy-paste, and faster analysis with current market inputs already in the workbook. For a wealth advisor reviewing a client portfolio, it means easier access to current pricing, performance, risk and market context to support faster, more informed client conversations. Prompts to try: Pull current FX spot rates for EUR/USD, GBP/USD, and JPY/USD from LSEG into a new sheet. What would it cost to roll our six-month forward hedges on EUR/USD out another six months? Pull the forward points from LSEG and show the all-in rate. Bring in the USD swap curve from LSEG so I can model the impact of issuing 10-year debt at current levels. Moody’s The Moody’s connector brings credit ratings, research, entity data, and news into Excel so teams can work with decision-grade credit intelligence alongside the rest of their model. Whether you’re evaluating an issuer, pressure-testing exposure, or building a credit view for internal stakeholders, you can bring trusted credit context directly into the workbook instead of piecing it together across systems. Prompts to try: Pull the latest Moody’s rating, outlook, and recent research for each company in the portfolio, then summarize the key credit considerations in a new column. For each issuer in column B, pull the Moody's company profile, 5-year financial summary, peer group, and sector outlook — then flag any peers where the sector outlook is negative. For the issuers in this portfolio, bring in Moody’s sector outlook, recent news, and any notable credit risks so I can compare exposures across the list. Availability LSEG and Moody’s connectors are available starting today in Excel for Web, Windows, and Mac for commercial customers with a Microsoft 365 Copilot license. MCP servers and agentic solutions are available through a Bring Your Own License (BYOL) model, with customers licensing directly from partner services. Commercial marketplace availability will follow. Learn more Learn more about LSEG Learn more about Moody's Learn more about federated Copilot connectors Learn more about Copilot in ExcelExcel Esports Comes to Amsterdam: Inside the 2026 European Open
Picture this: a packed venue in central Amsterdam, mechanical keyboards at the ready, a live audience, two days of competition, and on the big screen — a spreadsheet. Yes, a spreadsheet. What followed left no doubt that Excel esports belongs on a live stage. May 22–23, 2026 brought the global Excel esports community to the H20 Esports Campus in Amsterdam for the very first Excel Esports European Open, and what unfolded was equal parts world-class competition and community celebration. Organized by Financial Modeling World Cup (FMWC) as part of the Microsoft Excel World Championship (MEWC) circuit, the European Open put a €12,500 prize fund on the line across five formats — and, more importantly, served as a direct seeding round for the 2026 Microsoft Excel World Championship Finals in Las Vegas later this year. The field showed up ready. The flagship Main Event is exactly what it sounds like: top competitors on the circuit, head to head, on the clock. After two days of qualifying rounds and high-pressure eliminations, Diarmuid Early (Ireland) walked out as the inaugural European Open Main Event champion, with Sergio Trifiletti in second and Alexander Freedman rounding out the podium. If you follow the circuit, those names will be familiar — and finishing on top of that lineup is no small thing. From there, the weekend opened up across three more open formats, each with its own flavor. Team Relay turns Excel into a relay race — three-person teams sharing one workbook and a single clock — and team Titanic (Diarmuid Early, Michael Jarman, Jean Wolleh) took the title with a clean, well-paced run. Teams The Crucible and Oachkoatzlschwoaf finished second and third. Mixed Doubles, one of the more-watched formats on the circuit, pairs two competitors working in parallel on linked problems with every keystroke up on the big screens; Emilie Williams & Coby Dombrowsky took that trophy. Mega Elimination, the bracket-style knockout where short rounds leave very little time to overthink, went to Diarmuid Early. The Microsoft Excel Collegiate Challenge (MECC) Student Finals brought the next generation onto the European Open stage, and Benjamin Weber of FH Technikum Wien became the first-ever MECC European Open Champion — finishing his case with six minutes still on the clock, to a genuine roar from the arena. Luke Peyton (Messiah University) and David Montani Schnickmann (EY) rounded out the student podium. The student side of the circuit continues to grow, and Amsterdam was a great look at where the next wave of talent is coming from. Beyond the trophies, what happened in Amsterdam carries real consequence for Vegas. Diarmuid Early secured a direct seed into the MEWC Semifinals, with the rest of the Main Event finalists earning Quarterfinal spots — and the leaderboard going into the Finals just got a lot more interesting. Congratulations to the 2026 European Open champions: Diarmuid Early — Main Event champion Titanic (Diarmuid Early, Michael Jarman, Jean Wolleh) — Team Relay champions Emilie Williams & Coby Dombrowsky — Mixed Doubles champions Diarmuid Early — Mega Elimination champion Benjamin Weber — MECC Student Finals champion Historic first: Diarmuid Early walked out of Amsterdam with three trophies. Main Event. Team Relay. Mega Elimination. An unprecedented showing on the Excel esports circuit. And to everyone who made the trip — every player who sat down on that stage, under the lights and on the clock, deserves real recognition. Competing in Excel at this level, in front of a live crowd, takes guts. The depth of the field this weekend was a statement. A big thank you to the Financial Modeling World Cup team led by Andrew Grigolyunovich for putting the event together, and to the case authors and volunteers who kept two days of live competition running smoothly. Now: deep breath, sharpen your shortcuts, and we'll see you in Vegas.
