Copilot or Copilot Cowork - Which tool to use - and When
Microsoft 365 Copilot vs Copilot Cowork: Choosing the Right AI for Work As organizations expand their use of AI to improve productivity and automate business processes, understanding which tool to use—and when—is critical. Microsoft offers two complementary capabilities: Microsoft 365 Copilot and Copilot Cowork. While they both leverage AI to support work, they are designed for fundamentally different types of tasks. Two Different Models of AI Assistance Microsoft 365 Copilot is designed as a day-to-day productivity assistant embedded within familiar Microsoft 365 applications such as Word, Excel, PowerPoint, Outlook, and Teams. It works alongside users in real time, helping them create, summarize, analyze, and refine content. The user remains in control of each interaction, guiding the AI step by step. Typical use cases include: Drafting and improving documents Summarizing emails and meetings Preparing presentations Analyzing information across work content This model is optimized for frequent, interactive assistance where the user actively directs the workflow. Copilot Cowork, by contrast, is designed for execution-based workflows. Instead of responding one step at a time, users define a desired outcome, and Cowork independently plans and executes the necessary steps to complete the task. It can operate across multiple tools, gather information, and produce finished outputs such as documents, emails, or Teams posts. It is especially suited for: Multi-step workflows Scheduled or recurring tasks Event-triggered processes (such as responding to incoming emails or messages) Longer-running automated business processes Key Difference: Interaction vs Execution The primary distinction between the two lies in control and autonomy: Microsoft 365 Copilot supports guided, interactive work where the user drives each step. Copilot Cowork executes defined workflows end-to-end with minimal intervention, pausing only for approvals when needed. In short: Copilot = assist in doing the work Cowork = do the work Pricing and Usage Model The two systems also differ in how they are consumed: Microsoft 365 Copilot is licensed per user, providing a predictable cost structure for ongoing everyday productivity assistance. Copilot Cowork operates on a usage-based model using Copilot credits. These credits are pooled at the tenant level and consumed based on task complexity, frequency, and execution requirements. Organizations can manage usage through budgets, alerts, and governance controls. Choosing the Right Tool A simple decision approach helps determine which tool to use: If the task involves creating, summarizing, analyzing, or understanding information within normal work activities, Microsoft 365 Copilot is the appropriate choice. If the task requires multi-step execution, automation, scheduling, or event-driven workflows, Copilot Cowork is more suitable. If Microsoft 365 Copilot can complete the task effectively under user direction, it should remain the default option. Cowork should be reserved for higher-value, process-oriented automation where autonomous execution delivers clear business value. Governance and Responsible Use Because Copilot Cowork consumes metered credits, organizations are encouraged to implement governance controls before scaling usage. This includes: Spending policies and budgets Usage alerts and monitoring Credit limits and cost management strategies This ensures that automation is aligned with business value and resource consumption is properly managed. Summary Microsoft 365 Copilot enhances everyday productivity by assisting users within their workflow, while Copilot Cowork extends AI into autonomous execution of structured business processes. Together, they provide a layered approach to AI in the workplace—balancing human-guided assistance with scalable automation. Choosing the right tool depends on the nature of the work: interactive support versus end-to-end execution. When used appropriately, both can significantly improve efficiency and operational effectiveness across modern organizations.Claude + GPT | Multi-model intelligence in Copilot
Generate briefing documents, presentations, and Excel files from a single prompt with Copilot Cowork, pulling from your emails, calendar, and SharePoint through Work IQ — and fold in new tasks mid-run without stopping. Using Copilot Cowork, you can use the same platform that powers Claude Cowork. It’s designed for long-running, multi-step task automation. Use Critique in Researcher to pair a generation model with a dedicated review model, applying source reliability and evidence grounding before the report lands. Run model Council to submit one prompt to GPT and Claude simultaneously and compare their full reasoning side-by-side. These experiences with Copilot Cowork and Researcher are available now if your organization has the Frontier Program enabled. Jeremy Chapman, Microsoft 365 Director, shares how to choose, direct, and compare the right AI model for every task, all from within Microsoft 365. One prompt. Three files. Copilot Cowork generates your briefing doc, presentation, and Excel output — grounded in Work IQ data and saved directly to OneDrive. Try it now. Copilot Cowork handles new requests mid-run. Add meeting scheduling or an email update partway through and it integrates them into the active plan. Check it out. No more copy/paste into unmanaged AI sites. Work IQ automatically supplies Cowork and Researcher with your emails, calendar, Teams transcripts, and SharePoint files. Every output is grounded in your actual data. See how it works. QUICK LINKS: 00:00 — Copilot capabilities 01:06 — Copilot Cowork 02:32 — Mid-Run Task Injection 03:05 — Output 04:17 — Researcher Critique: Dual-Model Pipeline 05:58 — Work IQ Auto-Retrieval 06:58 — Model Council 08:50 — Wrap up Link References Try it at https://microsoft365.com/copilot Unfamiliar with Microsoft Mechanics? 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Copilot has options from Anthropic and OpenAI available directly from Microsoft 365. Using Copilot Cowork, you can use the same platform that powers Claude Cowork. It’s designed for long-running, multi-step task automation and it’s grounded by Work IQ, so you don’t need to move files and data outside of Microsoft 365 to other potentially unprotected services. Researcher has also been expanded with multi-model intelligence, where the new Critique capability separates the models, with one used to generate and another to refine its research outputs. And the new Council capability lets you submit a single prompt and view a side-by-side comparison across multiple model outputs. -Now, these experiences with Copilot Cowork and Researcher are available now if your organization has the Frontier program enabled, and today I’ll go hands-on with each while explaining the mechanics of how they work. Let’s start with Copilot Cowork. So in this example, I need to prepare for a customer meeting, and I want Cowork to build me a briefing document in Word, a PowerPoint presentation, and an Excel file with customer insights. I already have Copilot pinned with my agents and it’s opened. -Before I start, I’ll show you what’s set up in the knowledge sources. I can access information on the web, from people, and from Work IQ, so it doesn’t rely on connectors to access my work files, calendar, or previous meetings. Now I’ll paste in my prompt with links to reference files so it can help me then prepare for my meeting, and I want Copilot to pull in details from relevant emails and my calendar. I’ve also referenced an existing briefing document template as an example to follow, as well as an Excel overview with customer-specific metrics and visuals. And I want it to create a new briefing document as well as a client-ready PowerPoint presentation with our differentiators and recommended next steps. -So now I’m going to kick off the process and Cowork will show its progress, its inputs and outputs on the upper right-hand side of the screen. Cowork will then reason through all of the inputs and tasks from my prompt, then systematically work through everything until it generates the files that I requested. And it’s not only using the files referenced, but also searching across my Work IQ information. As it works, I can even request more tasks while it’s running. -For example, I can ask it to schedule prep time with people on my team and send an email status update to the account team. Cowork just folds that into the plan and keeps going. It checks schedules, and here’s the meeting it proposes for me and Riley on my team to review, and I’ll create that right from here. Then it authors an email to Ellis from the account team that I can choose to edit manually if I want. I’ll go ahead and add a thank you in line and then hit send. This can process for several minutes, so to save a little time, I’ll move on to when everything is complete. You’ll see that on the right in the output folder, it’s created a Zava client presentation, a customer briefing doc, and also a customer overview Excel file. -Now, I’ll open up the briefing document first, and it has everything relevant to the meeting and it uses our standard briefing template. In fact, if I open up the original one, you can see just how close the formatting is. Now I’ll open the presentation it generated. It explains our work at a glance, with key metrics from Work IQ and referenced files, as well as revenue and growth highlights. Now if I move on to the generated Excel file and open that, it’s laid out our year-over-year performance and used it to create forecasts for this year. We can also see the growth trends over time, and if I click into Sales by Category, we can even see a detailed breakdown across different product lines with comparisons for the last two years. And as it worked on my behalf, everything was saved directly into OneDrive, so it’s protected and can be shared with my team like any other Microsoft 365 file. -Next, one of the most powerful experiences in Copilot, Researcher, has also added new multi-model intelligence capabilities in addition to its options for using Claude from Anthropic or GPT from OpenAI. Researcher now takes us a step further with Critique by using a combination of models to separate generation from evaluation tasks, where one model leads the generation phase, planning the task, iterating through retrieval steps, and producing an initial draft, while the second model then focuses on review and refinement, acting like an expert reviewer before the final report is presented to you. This is now the default experience, and having these models work together helps ensure higher-quality outputs. Let me show you. -From Copilot and Microsoft 365, I already have Researcher open. At the top right, I’ll expand the model picker and explain the options. Choosing Auto will automatically generate responses using Critique with the two models working together. Under that is an option for Model Council that I’ll walk through in a moment. Then there are also options to choose GPT and Claude as standalone models. So I’m going to keep Auto in this case, and then I’ll paste in my prompt to generate an executive brief about the competition in our industry and where there might be expansion opportunities. Now, this is a very research-intensive request that will need to retrieve, evaluate, and analyze many resources via Work IQ and the web. -Now I’ll submit my prompt to get it started. Researcher can take several minutes to research and reason over a topic and generate its response, so to save a little time, I’ll move to its output. On the top I can see the content was generated by GPT and refined by Claude. First, there’s an executive summary about the market-related conditions. As I scroll down, you can see it’s assessed source reliability, where it focuses on reputable, authoritative, and domain-appropriate sources. Then as I continue scrolling, it’s also assessed report completeness, where the reviewer model ensures that the final report satisfies the request, along with relevant insights. -As you can see with the rest of the citations, it’s enforced strict evidence grounding, making sure that every key claim is anchored to a reliable source. So for example, here you can see that it’s pulled in structured data from an Excel file with detailed financials and several relevant Word documents from our internal SharePoint sites. And it’s done all of this research automatically without me having to manually reference or upload files into my prompt. Both models work together in this case to improve the generated output. Next, let’s move on to Model Council in Researcher. Now, this lets you compare responses from different models side by side so that you can see where they agree, where they don’t, as well as what differentiates each model. -So I’m back in Researcher, and this time from the model picker, I’ll choose Model Council. From there, I’ll just paste in my detailed prompt, in this case to review our latest customer feedback interviews to find the top themes and give recommendations based on our current plans in motion. Again, this is going to leverage Work IQ to find and analyze recent Teams meeting transcripts, our product plans from files and SharePoint and more as research sources, and it’s a lot to process. Everything looks good here, so I’ll go ahead and send it. And in this case, Researcher asks clarifying questions to better understand my goal. -So I’ll choose a short one-to-five-page report length. Then below that I’ll type “Go ahead” and it gets to work. I only need to submit my prompt one time for both models to process it simultaneously. Again, this process can run 10 or more minutes, so I’ll skip to the output. You can see that each model has its own tile on top, and you can click into any of them to view their outputs. Below that is a summary for how each model did, comparing their responses. And I can also view a full output for each model. So I’m going to drill into the GPT output, and that shows me a split-screen view with the GPT tab open on the right, and I can scroll its results and I can look at its structured reasoning and its response and all the details. -Now moving to the Claude tab, I can also look at its detailed response and reasoning and everything that it performed to derive the output. I don’t need to run separate prompts to find the model that I prefer. Now Model Council helps do that work for me. So now Copilot and Microsoft 365 gives you direct access to leading models, including Anthropic and OpenAI, with multi-model intelligence and without having to switch between platforms. -To get started, enable the Frontier program in your Microsoft 365 environment. Then go to microsoft365.com/copilot or use the mobile app to try it out. And keep watching Microsoft Mechanics for the latest tech updates, and thanks so much for watching.
