Issue on Copilot studio Credit Consumption
Hello Community, We are currently using a Copilot Studio license (€10/month plan) and have encountered an issue when using our agent. Although our organization still has a significant number of Copilot credits available, the agent displays the following error message: "You are out of credits." To verify the credit status, we checked the Power Platform Admin Center, where Copilot credit consumption is monitored. The current usage details are: Total credits purchased: 1,281,000 Credits consumed: 427,737 Remaining credits: Approximately 853,263 Based on these figures, we still have around 800,000+ credits remaining, yet the agent is unavailable due to the "out of credits" error. We would appreciate any guidance on the following: Why is the agent reporting that we are out of credits when a large credit balance remains? Are there any known limitations, allocation settings, or licensing requirements that could cause this behavior? Are there any troubleshooting steps we can perform to verify whether the credits are correctly assigned and available for use? Has anyone else experienced a similar issue, and if so, how was it resolved? Any guidance or recommendations would be greatly appreciated. Thank you.Copilot, Microsoft 365 & Power Platform Community call
💡 Copilot, Microsoft 365 & Power Platform weekly community call focuses on different use cases and features within the Microsoft 365 and Power Platform - across Microsoft 365 Copilot, Copilot Studio, SharePoint, Power Apps and more. Demos in this call are presented by the community members. 👏 Looking to catch up on the latest news and updates, including cool community demos, this call is for you! 📅 On 1st of October we'll have following agenda: Latest on SharePoint Framework (SPFx) Latest on Copilot prompt of the week PnPjs CLI for Microsoft 365 Dev Proxy Reusable Controls for SPFx SPFx Toolkit VS Code extension PnP Search Solution Demos this time Siddharth Vaghasia – How to create a Power Automate Approvals dashboard with SPFx David Duncan – Crafting SharePoint Search for improved user experience Asif Rehmani – Mind Reading 101: Use Microsoft Clarity to see behavior analytics of your SharePoint users 📅 Download recurrent invite from https://aka.ms/community/m365-powerplat-dev-call-invite 📞 & 📺 Join the Microsoft Teams meeting live at https://aka.ms/community/m365-powerplat-dev-call-join 💡 Building something cool for Microsoft 365 or Power Platform (Copilot, SharePoint, Power Apps, etc)? We are always looking for presenters - Volunteer for a community call demo at https://aka.ms/community/request/demo 👋 See you in the call! 📖 Resources: Previous community call recordings and demos from the Microsoft Community Learning YouTube channel at https://aka.ms/community/youtube Microsoft 365 & Power Platform samples from Microsoft and community - https://aka.ms/community/samples Microsoft 365 & Power Platform community details - https://aka.ms/community/home 🧡 Sharing is caring!Copilot, Microsoft 365 & Power Platform product updates call
💡Copilot, Microsoft 365 & Power Platform product updates call concentrates on the different use cases and features within the Microsoft 365 and in Power Platform. Call includes topics like Microsoft 365 Copilot, Copilot Studio, Microsoft Teams, Power Platform, Microsoft Graph, Microsoft Viva, Microsoft Search, Microsoft Lists, SharePoint, Power Automate, Power Apps and more. 👏 Weekly Tuesday call is for all community members to see Microsoft PMs, engineering and Cloud Advocates showcasing the art of possible with Microsoft 365 and Power Platform. 📅 On the 29th of September we'll have following agenda: News and updates from Microsoft Together mode group photo Reetik Chandra – Beyond the Link: Full Fidelity SharePoint News in Viva Engage Sarah Critchley & Ricky Castaneda – How to use Teams Client capabilities with the Agents SDK using the new Teams extension Vesa Juvonen – Building UX for Copilot – Modernizing Customer Resolution process 📞 & 📺 Join the Microsoft Teams meeting live at https://aka.ms/community/ms-speakers-call-join 🗓️ Download recurrent invite for this weekly call from https://aka.ms/community/ms-speakers-call-invite 👋 See you in the call! 💡 Building something cool for Microsoft 365 or Power Platform (Copilot, SharePoint, Power Apps, etc)? We are always looking for presenters - Volunteer for a community call demo at https://aka.ms/community/request/demo 📖 Resources: Previous community call recordings and demos from the Microsoft Community Learning YouTube channel at https://aka.ms/community/youtube Microsoft 365 & Power Platform samples from Microsoft and community - https://aka.ms/community/samples Microsoft 365 & Power Platform community details - https://aka.ms/community/home 🧡 Sharing is caring!
Copilot Studio agents problems connecting to Sharepoint knowledge source
Hello, Since last week users in my tenant are experimenting issues regarding the connection between copilot studio agents and Sharepoint. The agents are not able to extract information from Sharepoint sites, printing there is not information in the Sharepoint site regarding the user's question when that information is in Sharepoint. These agents used to work well till last week. Does have been any update in Microsoft 365 services that can be affecting these agents ability to retrieve information from Sharepoint?
Work IQ (Preview) in Copilot Studio not retrieving recent Teams/Outlook information
Hi All, We are building a POC in Copilot Studio where an agent tracks project information from Planner, Teams chats, and Outlook emails. We are using Work IQ (Preview) to retrieve information related to specific projects from Teams and Outlook. For example, if I send an email containing SOW details for Project A and later ask the agent "What are the latest updates/SOW details for Project A?", Work IQ sometimes does not retrieve the new email even after 30 to 75 minutes. We understand that Work IQ is currently in Preview, but we wanted to understand: Is there a documented indexing/sync delay for new Teams messages or Outlook emails? How long does it normally take for recent content to become available to Work IQ? Is there any way to improve or force the refresh? Is there any official Microsoft documentation regarding data freshness? Is there any workaround using Work IQ only? We are specifically evaluating Work IQ, so please don't suggest Graph API. 😅 Any guidance, documentation, or experience with a similar scenario would be really helpful. Thanks in advance!Governance is becoming agentic, too: How enterprises can operate AI at scale
Organizations have spent the past few years trying to get people building with AI. That effort is working: Agents are moving beyond experimentation and into real business processes. For IT teams, this kind of successful adoption creates a new set of questions. What agents exist across the organization? Who owns them and what systems and data can they access? How are they being used, and what do they cost to operate? Are they healthy? And how do you know when an agent’s risk profile or behavior changes? These questions get harder as the agent estate of an organization grows. Agents may be built by different teams or on different platforms. Some may operate outside the Microsoft ecosystem entirely. Their capabilities can also change as they connect to new data and tools. We’ve been thinking a lot about this challenge as we prepare for the Microsoft Power Platform Conference (PPCC) in October 2026. One idea comes up again and again: Scaling agents doesn’t just mean governing more things. It requires changing how governance itself works. Inventories, reviews, and administrator controls remain important. But they need to become part of a more continuous operating model. I see that evolution in three parts: observe continuously, respond proportionately, and automate where appropriate. Observe continuously You can’t govern what you can’t see. And when it comes to agents, visibility means more than maintaining an inventory. It means understanding each agent in context: its ownership, identity, access, usage, health, and behavior. It is important to note that that context isn’t static. A maker or admin could give an agent access to a new tool or data source. They could change the agent's owner. The way people use it in production may reveal something about the build that wasn’t apparent during development. And, of course, usage of that agent (hopefully) will grow over time. That makes observability, defined as visibility into agent activity and behavior through telemetry, an ongoing requirement. Then, at enterprise scale, there’s the question of coverage. In my experience, many enterprises plan to build agents in multiple places. They may be built with Microsoft platforms like Copilot Studio, third-party platforms, and/or custom development. This is where cross-platform management layers like Microsoft Agent 365 become especially important. A shared agent control plane—that is, a common layer for managing and governing agents across platforms—makes observability actionable across the agent estate, rather than leaving signals isolated within individual platforms. IT can use those signals to detect changes such as risk, usage, cost, and health over time. isualize how agents fit into the broader ecosystem, connect with other agents, and perform over time to simplify monitoring and resolve issues quickly. At PPCC, the Agent 365: Securely Managing and Governing Agents at Scale workshop will go deeper into the controls and operating practices behind this model. If these are questions you’re working through in your organization, I hope you’ll join us there. Respond proportionately Once you have signals, the next question is what you do with them. Not every agent represents the same level of risk. An agent that answers employee questions from approved internal documentation is very different from one that can access sensitive data and take actions in a production system. They shouldn’t necessarily go through the same governance process. At enterprise scale, treating every agent identically creates problems in both directions. Too little oversight introduces unnecessary risk. Too much can create bottlenecks for scenarios that fit established policies. A more scalable approach is to align the response with the risk. Identity, permissions, data access, autonomy, and available actions all provide useful context. Organizations can use that content to determine which policies apply and where additional review is appropriate. For example, imagine an agent gains access to a new data source. That change is a signal. What’s the appropriate response? If the new access falls within established policies and risk boundaries, the agent may not need additional intervention. If it introduces a higher level of risk—such as access to sensitive data—it could trigger stronger controls or human review. This type of program might look something like this: The important shift seen with this approach is that governance becomes less dependent on applying the same manual process to every agent. Instead, organizations can establish patterns for different levels and types of risk. That makes governance more predictable for builders, too. Teams know the boundaries they’re working within, while higher-risk agents can receive additional scrutiny. We’re applying this principle inside Microsoft as well. At PPCC, How Microsoft Does IT: Managing and Governing Agents with Risk-Aligned Oversight will share how we’re approaching risk-aligned agent governance across Copilot Studio, Agent 365, Microsoft Defender, and Microsoft Purview. Automate where appropriate Once you can observe changes and determine the appropriate response, the next question is: Does a person need to execute that response every time? At enterprise scale, the answer increasingly needs to be no. Many governance decisions are repeatable. Organizations already know the policies they want to enforce, the boundaries agents should operate within, and the conditions that require additional review. This is where I think governance starts to become agentic, too. One useful way I’ve found to think about it is as a continuous loop: Observe → assess → act → escalate At a high level, this loop represents how a more automated governance framework can work. Basically, in such a framework: The governance system detects a relevant signal and evaluates it against the context and policies the organization has established. When the appropriate response is clear, an automated control can act. When the situation falls outside those boundaries or requires judgment, it can be escalated to a person. The goal isn’t to automate every governance decision, but rather to automate the decisions we already know how to make. People will continue to be responsible for setting policies, defining risk tolerances, and deciding where human judgment is required. The objective here is to let automation handle more of the repeatable work inside those boundaries. In practice, that changes the job of IT teams and Centers of Excellence (CoEs). Instead of inspecting and configuring agents one at a time, they can spend more of their effort designing how governance operates: defining trusted patterns, establishing risk thresholds, and deciding when human intervention is required. You can see some of this shift from visibility toward action at PPCC. The Agentic Governance: Secure, Govern, and Operate Your Power Platform at Scale session will explore real-time inventory and telemetry alongside automated controls and security, using the Power Platform API as an extensibility layer for enterprise governance. Governance must evolve with the agent estate The goal isn’t a future where people disappear from agent governance. It’s one where their attention is used more deliberately. As agents become more capable, the systems around them need to become better at sensing change. As the estate grows, oversight needs to reflect actual risk. And as routine governance work increases, organizations need to decide what can be handled through established policy and what needs human judgment and accountability. That is the shift I mean when I say governance is becoming agentic, too. And we’re only beginning to explore what that operating model can look like at enterprise scale. If you’re working through these questions in your own organization, we’ll be digging into them throughout PPCC. Here are a few sessions and workshops I recommend: Sessions Governance of All Your Agents at Scale How Microsoft Does IT: Managing and Governing Agents with Risk-Aligned Oversight Observability and Governance for Your Third-Party Agents with Minimal Configuration and Maximum Control Secure by Design: Preparing Agents for Production and Scale Governance First, Agents at Scale: How Wells Fargo Built Copilot Studio Agents in a Regulated Bank Workshops Agent 365: Securely Managing and Governing Agents at Scale Mastering Governance at Scale: Unlock the Full Potential of Your Power Platform and Agent Estate Nobody Knows How Many Agents You HaveMore powerful agents and workflows for autonomous business processes: Introducing a new harness for Copilot Studio
Over the past two months, we’ve been previewing a new capability within Copilot Studio that lets you build agents capable of taking on more complex business processes. Today, we’re excited to share that this capability is now generally available for production use and to introduce its new name: the GitHub Copilot harness in Copilot Studio. Meet the GitHub Copilot harness The GitHub Copilot harness gives Copilot Studio the coding and reasoning capabilities behind our most advanced agent experiences (like Copilot Cowork and the GitHub Copilot coding agent). This means your agents can now handle work that used to be out of reach, including processes that have many steps, many sources, and ambiguous decision points. The new harness is built for complex, long-horizon work using the latest frontier reasoning models like Opus 5, GPT-5.6 Sol, and Fable 5. It can plan, reason through dynamic problems, run an agentic loop, use skills, integrate workflows, connect to tools and agents in other platforms, and produce rich, multi-part outputs. In our own testing with real world business process evals, Copilot Studio shows significant performance and quality gains when using the GitHub Copilot harness. Improvements in multi-tool use, file analysis, code analysis, and knowledge quality mean these agents are more capable of taking on your most complex business processes. To help you build these more capable agents, we’re also delivering new experiences for makers building agents with the GitHub Copilot harness. The agent designer is more intuitive for authoring, putting the most important tools right within reach to make authoring faster, while retaining full agent lifecycle management features. Then, the workflow designer gives a visual canvas to understand and edit workflows, including adding agent nodes and running workflow evals. And soon, natural language authoring will let you describe your business goal and assemble the right combination of agents and workflows through a multi-turn conversation. Agents running on the GitHub Copilot harness use usage-based billing for all work, regardless of Microsoft 365 Copilot licensing. You pay for your agent’s usage based on the models you choose, the organizational context and tools you add, and runtime used. Certain AI-driven maker experiences, like natural language authoring, evaluations, and testing, will also fall under usage-based billing if building with the GitHub Copilot harness. You can learn more about Copilot Studio usage-based billing here. Continued Support for Copilot Chat and Standard harnesses Adding a new harness does not change the ones you already rely on. Different harnesses can be optimized for different outcomes, so rather than relying on a single one-size-fits-all approach, Copilot Studio now lets you choose the harness that best fits your scenario. This means Copilot Studio supports three harnesses today: The Copilot Chat harness, which uses the same harness as Microsoft 365 Copilot Chat and is ideal for customizing Copilot Chat experiences. The Standard harness, which most agents built in Copilot Studio use today and is great for conversational agents with rules-based topics. The new GitHub Copilot harness, which uses the power of GitHub Copilot SDK to automate complex, agentic business processes. We will continue to support the Copilot Chat and Standard harnesses in Copilot Studio for both existing agents and authoring of new agents. Microsoft 365 Copilot licensed users continue to benefit from fair use of Copilot Chat or Standard harness agents included in their Microsoft 365 Copilot license. For all other usage, the Copilot Chat and Standard harnesses will continue to be billed using the existing fixed rate card. Get started today The GitHub Copilot harness is generally available now, and you can start creating these agents directly from the Copilot Studio homepage. We can’t wait to see what you build. Share your thoughts using the feedback control in the top right corner of the product. Your input directly shapes what we build—and how you build—next. Try Copilot Studio today!
Adding a shared connected-agent bot to a solution pulls in all parent bots, no way to exclude?
I'm trying to add a single Copilot Studio bot to a solution, and it's pulling in every other bot that references it as a connected agent with no prompt and no way to include just the one bot. Repro: 1. Created a brand-new, empty solution (single publisher, no components added yet). 2. Objects → Add existing → Bot → selected only "agent_1" 3. No "include required components" dialog appeared the add just happened. Expected: the solution contains only the selected bot (at most, plus its own connection references). Actual: the solution jumped to 238 objects, 6 agents, 229 agent components, 3 connection references. It pulled in every other bot in the environment that has a connected-agent action pointing at "agent_1" (5 parent bots), plus their own further connected-agent dependencies. This makes it impossible to build a scoped solution around one client-facing agent when it shares a connected-agent bot with unrelated agents elsewhere in the tenant. Normal Dataverse solution dependencies pull in what a component requires; this also seems to pull in everything that depends on it, in reverse, with no override. Questions: 1. Is this expected/intended behavior for connected-agent solution dependency tracking? 2. Is there any supported way UI, PAC CLI, or Dataverse API to add a shared connected-agent bot to a solution without including every bot that references it?Getting Started with Copilot Studio: Your PAA & FAQ Guide
What is Microsoft Copilot Studio? Microsoft Copilot Studio is a low-code, graphical tool within the Power Platform used for building and conversational bots. It empowers users, even those without extensive technical backgrounds, to create sophisticated logic and connect to various data sources and services using prebuilt or custom plugins. Is Copilot Studio easy to use for beginners? Yes Copilot Studio is designed to be easy for beginners. You only need to describe the agent you want in plain language to start creating it. The platform uses a graphical, low-code interface that streamlines the process of defining instructions, knowledge sources (like documents), and conversation triggers, making it accessible to most users. What is the difference between Microsoft 365 Copilot and Copilot Studio? Microsoft 365 Copilot is an AI assistant that integrates across Microsoft 365 apps (Word, Excel, Teams, etc.) to enhance productivity. Copilot Studio, conversely, is a development platform used to build customised AI agents that are tailored to specific business goals or data sources. Copilot is the agent you use; Copilot Studio is the tool you use to build or extend agents. Do end-users need a specific license to use a Copilot I create? Yes, licensing for end-users depends on how and where the custom copilot is deployed. While development often requires a Power Platform or Azure subscription deploying the bot across an organization may require specific Copilot licenses for the end-users accessing the agent. Check the official Microsoft licensing documentation for your specific scenario. How can I add SharePoint data as a knowledge source for my Copilot? You can connect your Copilot agent to SharePoint data using the generative answers feature in Copilot Studio. The agent can search documents stored in a SharePoint document library. Be aware that there can sometimes be nuances with how attachments versus core document libraries are indexed, which the community is actively discussing in the forums. We hope this formatted FAQ helps you quickly find the information you need! If you have more questions, please use the discussion board to connect with the community. This Blog Post Was Drafted With The Help Of Artificial Intelligence On The Copilot Studio User GroupChild agents and local agents in Copilot Studio
I'm AI administrator, and I have a colleague who've build an agent in Copilot Studio that uses to child agents. However on his screen they have the relationship "Local" and he can't access them or do anything. When I look at his agent, the sub agents have relationship "Child" and everything works fine. The image down below is what he sees - and the trigger also gets that orange triangle. Have anybody experienced the same? We tried to give another colleague editor permission to the agent, and that colleague experiences the same. They are both sitting at an office in another country than me.
