Copilot Studio is helping close the gap between idea and solution. What began as a way to create conversational experiences has evolved into a platform for transforming business processes end to end, equipped with the security, governance, and operational controls organizations need to move from experimentation to enterprise-wide adoption.

This month marks an important next chapter. With Copilot Studio, makers can now build apps, workflows, and agents in one place. Teams can bring together the interface people use, deterministic workflows the business may rely on, and agents that reason, adapt, and act—using each where it makes the most sense as part of one cohesive solution.

The September 2026 Copilot Studio updates build on that vision. They bring new ways to create business solutions, control sophisticated agents, connect them to enterprise knowledge, evaluate and prepare them for production, and extend what they can do.

Build complete business solutions with apps in Copilot Studio

Apps are now available in public preview in Copilot Studio, giving makers a new way to turn business needs into interactive experiences alongside agents and workflows.

Start by describing what you want to build in natural language, including the business outcome, intended users, data, and actions. Copilot Studio then generates a draft app that you can preview and continue refining conversationally, while retaining access to the underlying code when deeper customization is needed.

More importantly, apps make it possible to choose the right experience for each part of a business process. An onboarding solution, for example, might use an app to give managers and employees a structured interface, workflows to execute repeatable onboarding steps, and an agent to answer questions, handle exceptions, and adapt as circumstances change.

These experiences are supported by Microsoft Copilot Managed Runtime, now in public preview. Copilot Managed Runtime provides Microsoft-operated hosting, identity, governed data access, lifecycle management, Git-backed versioning, and centralized visibility for apps created across Copilot Studio, Copilot Cowork, and Copilot Code. That means organizations can make it easier for more people to build, without lowering the bar for running business solutions securely and reliably.

Add deterministic control to agents with hooks

Agents are valuable because they can reason and adapt, but some actions need to happen every time. Hooks, now in preview for agents powered by the GitHub Copilot harness, bring more control to agentic runs. While a workflow defines the logic to execute, a hook determines when that logic runs.

That distinction means makers can add deterministic control at key points in an agent’s lifecycle. Like topic triggers in the Standard harness, hooks provide a way to ensure specific logic runs consistently. In the GitHub Copilot harness, that extends to events like session start, tool calls, and errors.

For example, makers can use hooks to load required context when a session starts; inspect, modify, or block a tool call before it executes; transform results after a tool runs; or respond when something fails. Hooks can also capture consistent logging and telemetry throughout the agent’s run.

The result is more predictable agent behavior while preserving the flexibility of agentic reasoning. Logic that must run every time can run deterministically, while the agent remains free to reason and adapt around it.

Ground agents in reusable enterprise knowledge with Foundry IQ

The Foundry IQ integration with Copilot Studio is now generally available, giving organizations more ways to connect agents to enterprise knowledge.

A single Foundry IQ knowledge base can be reused across multiple Copilot Studio agents, while each agent can be configured with the knowledge sources and retrieval scope appropriate for its purpose. Agents can retrieve information from the knowledge base and provide grounded responses with citations, helping users verify the sources behind generated answers.

Organizations can also securely connect Copilot Studio agents to Foundry IQ through private networking, supporting enterprise network isolation and secure knowledge access.

Evaluate more dimensions of agent performance

Evaluations in Copilot Studio are expanding beyond agent conversations to automation. Makers can now evaluate both individual AI nodes and the broader automation, which helps teams understand whether processes are performing as intended and catch issues earlier. Custom graders and General Quality provide repeatable criteria for measuring results.

This broader scope also includes new ways to measure the aspects of agent performance that matter for each scenario. Task Completion checks whether an agent accomplished the intended user outcome, Tool Accuracy evaluates whether it selected the expected tools and inputs, and Safety measures responses against configurable content safety thresholds. Latency checks add response time results alongside quality results, as well.

For evaluation needs specific to a business or scenario, the new Custom Graders Library makes custom graders reusable across agents and test sets. Makers can also have Copilot Studio generate a custom grader for a specific agent and evaluation scenario, reducing the need to write the grading criteria from scratch. Generated graders are tenant-specific and visible only within that tenant.

Finally, a new Evaluation Viewer role lets reviewers and other stakeholders see evaluation results without requiring broader maker permissions.

Prepare agents for publishing with the Review panel

Evaluation can help you understand how an agent performs. The Review panel, now generally available, helps you assess agent readiness and identify what still needs attention before that agent is published.

Visible in the top menu bar during agent creation, the Review experience in Copilot Studio surfaces blockers and warnings throughout the building process, instead of waiting until a maker selects Publish. Issues are prioritized by severity and include explanations and, when possible, actions makers can take to resolve them. New evaluation warnings can also flag when an agent has never been evaluated, or when a model change means that previous evaluation results may no longer reflect its current behavior.

The Review panel can also surface organizational policy restrictions when makers encounter them and direct them toward organization-specific guidance when additional help is needed. The result is a focused set of relevant, actionable signals designed to help makers move from blocked to ready before publication.

Discover reusable capabilities with the centralized plugin registry

Microsoft recently introduced the plugin registry, a shared foundation for discovering and governing reusable capabilities across Microsoft Copilot experiences.

The registry already includes more than 100 plugins and brings skills, connectors, and agents into a common catalog that can be managed centrally. Integration across Microsoft experiences continues to expand, with Copilot Studio support rolling out over the coming weeks.

As the ecosystem expands, the plugin registry is designed to make capabilities easier to discover and reuse while giving organizations greater visibility and governance over how those capabilities are used.

Build your Copilot Studio skills

As Copilot Studio grows into one studio for building apps, workflows, and agents, there are more possibilities to explore—and more than one way to get started. Whether you’re just getting started or ready to develop more advanced skills, we’ve brought together resources to help you find your next step.

Explore what’s possible through demos and guided learning, learn by doing with hands-on Agent Academy projects, advance your skills with Microsoft Official Curriculum and credentials, and grow with personalized learning through AI Skills Navigator. You can start wherever you are and choose the resources that match what you want to build.

Not sure where to begin? Get started by registering for the Skill up on Microsoft Copilot Studio webinar.

Explore additional skilling opportunities in our guide about four ways to learn how to build with Microsoft Copilot Studio.

These new ways to learn arrive at the right time, as Copilot Studio expands what makers can build and the business processes they can transform—all on one agentic AI platform.

Apps give people an interface for getting work done. Workflows provide predictable execution where the business needs it. Agents reason, adapt, and act when the path forward isn’t predetermined. Capabilities like hooks, enterprise knowledge, evaluations, and agent readiness give makers more control and confidence as they put solutions into practice.

Want to see what building across apps, workflows, and agents looks like in practice? Watch Senior Product Manager Jack Rowbotham take a procurement process from prompt to production, using Copilot Studio to build, evaluate, and connect the pieces into one end-to-end solution.

That’s the vision of one studio for building the business: bringing the right building blocks together to transform a process from end to end. One studio. Apps, workflows, and agents working together to turn “how our business should work” into “how our business does work.” Get started with Copilot Studio.

The post New and improved: Build apps, extend agents, and transform business processes in Microsoft Copilot Studio appeared first on Microsoft Copilot Blog.

Functioning code is only the first step. The work that follows includes provisioning and securing cloud resources, configuring identity and security models, honoring organizational policies, and establishing deployment processes. Operating the app throughout its lifecycle can slow teams down, consume additional resources, and create a different governance model for every app-building platform.

Today, we’re introducing Microsoft Copilot Managed Runtime into public preview, an enterprise-grade platform to run code within the Microsoft 365 tenant boundary that’s governed by IT and inherits all the usability expectations users have such as sharing, live data connections, and easy access to their apps.

Copilot Managed Runtime already powers the apps built in Copilot Cowork, Copilot Code, and Microsoft Copilot Studio. We’re also enabling access to third-party tooling and professional developers, giving IT admins a consistent way to govern apps and giving users a familiar app experience, across build experiences.

More freedom to innovate, more confidence to run

The Copilot Managed Runtime host gives teams a shared enterprise foundation around the apps they create, bringing together Microsoft-operated cloud hosting, identity, governed data access, and lifecycle management. Instead of assembling that foundation for each application, teams can focus on putting useful apps into people’s hands, with IT retaining control over how those apps run, and who is able to build over which enterprise data sources.

Security and governance are part of that foundation: Microsoft Entra identity provides authorized access, while organizational policies govern the connectors, data, and endpoints applications can use. Automatic version and source control via Git enables true developer workflows and co-dev. Connectors and Work IQ are integrated to make accessing and authorization to the products and data you need easier.

Microsoft operates the platform; your organization sets the boundaries; you remain in control.

That consistency extends across apps built in Microsoft experiences such as Copilot Cowork, Copilot Code, and Copilot Studio as well as SDK-compatible third-party tools, with a centralized inventory in the Microsoft 365 admin center to review access, usage, health, and policy. Builders gain more freedom to create, while IT gets one management model rather than a separate approach for every app-building tool.

Bring your code and the tools you love

The Copilot Managed Runtime SDK is the connective layer between the code you create and the Copilot Managed Runtime host. It gives Microsoft and third-party development experiences a consistent way to build against Microsoft services and move an application from development into an enterprise-managed runtime.

The SDK and command-line interface (CLI) support the full development lifecycle rather than simply packaging the finished app. Developers can scaffold and configure projects, define the data connections their app needs, and generate typed services for working with connectors from TypeScript. They can run and preview applications during development, then deploy and version them through the same toolchain. At runtime, SDK APIs provide a secure bridge between the application and services exposed through the host, including governed access to enterprise data, identity, and Copilot work context.

Developers can continue working with editable, Git-backed code and familiar web technologies in the tools they already use, while giving the resulting application a consistent path to Microsoft 365 for deployment and operation.

With the Copilot Managed Runtime SDK, an app made with Lovable can now run inside your Microsoft tenant, the same way everything else does: same sign-in, same policies, same app inventory.

Lan Roche, Head of Global Partnerships at Lovable

Moving from a working app to a production app usually requires significant platform work. The Copilot Managed Runtime host makes that enterprise foundation part of the deployment model rather than a separate project at the end. Apps deployed to the host can use capabilities such as:

• Microsoft Entra identity and sharing.
• Microsoft-hosted runtime environments for applications.
• Organizational policies for connectors, data access, approved endpoints, and auditing.
• Deployment, versioning, and lifecycle controls.
• Central inventory, monitoring, usage visibility, and IT control.

Teams can preview and improve a new version while the current version remains available to users. Identity and policy are enforced through the host. Monitoring, usage, and inventory give your organization visibility into what’s been built, how apps are being used, and app health. Enterprise readiness becomes the default path, not a checklist that each development team must rebuild.

View, manage, and govern apps in a single place

As those who can build applications and how quickly they can be created keep expanding, that opportunity also raises a practical question for every organization: how do we keep a clear view of what’s running, who can access it, which data and services it can reach, and whether it continues to meet our policy?

Apps hosted with Copilot Managed Runtime appear in the new Apps experience in the Microsoft 365 admin center, giving administrators a central inventory and a consistent place to review access, usage, health, and policy. The same model applies regardless of where the app was built, so IT doesn’t need a separate governance playbook for every creation tool.

Central governance should not require centralized creation. Builders can continue to work in the right experience that fits their job. IT gets a common operating layer for deployment, security, monitoring, and lifecycle management. That separation of open build and managed run is what makes it possible to scale app innovation without scaling operational risk at the same rate.

Enterprise app development and governance scenarios

The Copilot Managed Runtime model supports a wide range of internal business applications. For example:

• A team can create a launch-management app in Copilot Cowork, connecting it to approved planning data, and deploy it through a governed path.
• A developer can pull the code down to continue to build upon what the team created with familiar web technologies and update it without forking or standing up a separate runtime, platform resources, and governance stack.
• An administrator can review the app in their inventory, monitoring usage in one place, and applying a consistent set of controls across applications from different build experiences.
• In each case, the enterprise operating model remains consistent regardless of the authoring toolsets used. That gives makers and developers more freedom throughout the lifecycle to build and iterate and gives IT more confidence once the application reaches users.

Get started with Copilot Managed Runtime in public preview

The Copilot Managed Runtime host and SDK are being introduced in public preview. Microsoft entry points are already live with Copilot Cowork, Copilot Code, and Copilot Studio, and developers can use the SDK and plugins to build applications for the host. Read more Copilot announcements on the Official Microsoft Blog.

Administrators can enable and disable apps and review the default policies in the Apps experience in the Microsoft 365 admin center.

AI will keep lowering the barriers to application creation. Trust, control, and reliability need to advance just as quickly. With the Copilot Managed Runtime host and SDK, teams get the freedom to build in the tools they choose, and organizations get a consistent way to deploy, secure, govern, and operate what those teams create, leaving your enterprise with apps built for work.

We look forward to seeing what you build.

The post Build where you want, run with confidence: Now Microsoft hosts and manages the code created by Copilot appeared first on Microsoft Copilot Blog.

At the center of the latest Copilot Studio updates is the general availability of the GitHub Copilot harness, the new foundation for building reasoning-heavy agents and workflows in Copilot Studio. Alongside the harness, recent updates add new ways for agents to use skills, memory, enterprise knowledge, workflows, model context protocol (MCP) servers, connected agents, files, and more.

Build agents and workflows for complex business processes with the GitHub Copilot harness

The GitHub Copilot harness is now generally available in Copilot Studio. This advanced harness is designed for reasoning-heavy agents and workflows that need to complete complex business processes.

The harness sits between the AI model and the agent or workflow you build, orchestrating how the components work together. It helps determine when to call the model, what context to provide, and which tools, MCP servers, or connected agents to use. This allows agents and workflows to plan steps and adapt their approach as they work toward the defined goal in a recursive manner. Basically, rather than relying on predefined paths, the agent or workflow can adjust its execution path based on the goal and the available inputs.

The harness also supports capabilities like skills and memory (see next section) and can natively create and edit Word, Excel, PowerPoint, and PDF files. Each task runs in a secure sandbox governed by Copilot Studio.

All this makes the GitHub Copilot harness particularly well suited for scenarios that combine reasoning with action across multiple steps. For example, an accounts payable agent could read invoices, match them to purchase orders, gather missing information, and route exceptions for approval.

The GitHub Copilot harness is available alongside the standard harness, so you can choose the foundation that best fits what you’re building. Learn more about choosing a harness.

Expand what your agents can do with skills, tools, and connected agents

The most useful agents can do more than answer questions. New capabilities for agents powered by the GitHub Copilot harness give you more ways to equip agents for the work you want them to perform:

• Skills let you package instructions into modular, reusable capabilities. Write a skill or upload an existing skill, add it to multiple agents, and share it with your teammates. This feature helps teams reuse proven approaches instead of rebuilding the same capability for every agent.
• For larger solutions, connected agents (in preview) let a primary agent delegate requests to specialized agents. This can help you create modular agent architectures where one agent serves as the front door and calls specialists for particular tasks.
• Now in generally available, you can also add workflows and MCP servers as tools. Workflows can give agents access to multistep deterministic automation, while MCP servers can connect them to external services and capabilities.
• With the Windows 365 for Agents MCP server, now generally available, agents can interact with a Windows 365 Cloud PC to work with desktop applications, browsers, and user interfaces.

The goal with these capabilities is to help teams move from building isolated agents to creating reusable, extensible agent solutions. Being able to build on proven components and specialized capabilities means complex agents are easier to develop, maintain, and scale across the organization.

Give agents richer context with knowledge, memory, and files

The right context can help an agent deliver more relevant responses and take more appropriate actions as it works.

With Work IQ in Copilot Studio (preview), agents powered by the GitHub Copilot harness can connect to organizational context such as emails, calendar events, files, Microsoft Teams messages, and people information. You can also connect an agent to Foundry IQ to use a knowledge base you’ve already built and tuned in Microsoft Foundry.

Memory (also in preview) adds another source of context by allowing an agent to retain relevant information from previous interactions with an individual user. When enabled, memory can capture preferences and patterns and apply them in later conversations, helping you build experiences that become more relevant over time.

Agents can also take on larger, more complex document-based work. Now in preview, users can give agents files to analyze and work with directly, unlocking scenarios that require agents to reason over substantial documents and use what they find to complete a broader task. Users can also view files the agent creates during the conversation.

These capabilities all help agents work with a deeper understanding of the organization, the task, and the individual user. That richer context can reduce the need for users to repeatedly supply information and help agents not only deliver more relevant responses, but support more complex, ongoing work.

Manage agents with greater visibility and control

New Copilot Studio capabilities give administrators more ways to manage agents within their existing security and governance practices. Recent updates strengthen agent-level identity, expand environment-level observability, and add new trust signals for MCP servers.

First, as of July 2026, Copilot Studio automatically creates a Microsoft Entra Agent ID for every new agent. This gives individual agents their own identity in Microsoft Entra and helps administrators apply identity and access controls at the agent level.

For agents using MCP servers, you can also now submit an MCP server for Microsoft certification. Certification provides customers and administrators with additional information that an MCP server has been evaluated against Microsoft expectations for areas including reliability, security, compliance, and responsible operation.

Finally, with environment-level agent telemetry, now in preview, administrators can export telemetry from Copilot Studio to Application Insights through the Microsoft Power Platform admin center. Use this feature to validate agent runs, monitor tool execution, create alerts, and build custom dashboards for operational analysis.

Together, these updates help organizations treat agents as governed enterprise assets, with clearer identity, trusted connections, and the operational insight administrators need to manage them confidently at scale.

Reach customers across voice and digital channels with real-time agents

Real-time agents are expanding capabilities and channels. You now have new options for where you deploy them, how you customize voice experiences, and how you monitor performance.

Previously available for voice experiences, real-time agents can now also be deployed to digital messaging channels. Currently in preview, this feature allows you to use the same agent configuration across voice and digital messaging to create more consistent, context-aware customer experiences without maintaining separate agents for each channel.

For voice experiences, you can now use GPT-5 Chat. The model, also in preview, uses a text-based voice architecture that converts speech to text, generates a response, and synthesizes it back to speech. This enables advanced voice customization with neural text to speech, as well as greater deployment flexibility.

Finally, you can monitor real-time agents with Application Insights in Azure Monitor, which gives you more visibility into agent performance and helps you identify and troubleshoot issues.

Learn more about real-time agents and best practices for managing them at scale.

More improvements to help you build

A few more Copilot Studio updates help make everyday agent authoring more flexible:

• Choose from more models. Claude Sonnet 5 and GPT-5.5 Chat are now generally available as primary models, giving you more options to match model capabilities to your agent scenario.
• Build with the right foundation for the job. With multiple harness options available in Copilot Studio, you can choose between reasoning-heavy, multi-step experiences and more structured, predictable agent scenarios based on what you need to build.

The latest Copilot Studio updates give makers more building blocks for agents that can reason, act, collaborate, and work with richer context—while giving organizations more ways to manage those capabilities as their agent ecosystems grow.

What comes next

The significance of these updates goes beyond any single feature. Copilot Studio now has more of the building blocks needed for agents to take on consequential business processes: stronger reasoning, reusable capabilities, richer context, more ways to act, and enterprise controls to support them.

That opens the door to a much broader range of agent use cases. As makers begin combining these capabilities in new ways, the question is shifting from what an agent can do toward what work an organization is ready to give it.

Stay up to date on all things Copilot Studio

More is coming across voice channels, workflows, and the building experience. Check out all the updates as we ship them, as well as new features releasing in the next few months here: What’s new in Microsoft Copilot Studio.

Reimagine business processes

Discover how AI agents can help your organization work smarter and move faster.

Explore Copilot Studio

The post New and improved: GitHub Copilot harness, agent skills, and richer context appeared first on Microsoft Copilot Blog.

AI agents are only as capable as the tools, skills, and information they can easily connect to. In sales, the intelligence that drives great decisions—buying signals, conversation insights, market and account context—often lives outside the customer relationship management (CRM). Getting it into the flow of work has traditionally meant costly integrations or data-duplication projects only the largest companies could sustain.

The Model Context Protocol, or MCP, is an open standard that lets AI agents securely connect to external tools, systems, and data sources. MCP helps organizations unlock the full value of their CRM data by connecting agents to the systems, tools, and knowledge they already use. It extends first-party agents, unifies fragmented business data, brings CRM intelligence into any experience, and accelerates the development of custom agents. For Dynamics 365 Sales, that means agents can securely tap trusted intelligence in real time without requiring sellers or IT teams to rebuild integrations or duplicate data. The value shifts from data plumbing to intelligent action, giving sellers and sales leaders a more complete, connected, and actionable experience inside Dynamics 365 Sales.

Our Microsoft-built sales agents in Dynamics 365 Sales—including the Sales Qualification Agent and Sales Opportunity Agent—are built on Microsoft Copilot Studio, where MCP tools plug in natively. You can bring your existing partners, licenses, and trusted data directly into Dynamics 365 first-party agent experiences without standing up new CRM integrations or duplicating data.

The result
Higher-value Dynamics 365 first-party agents that reason over trusted third-party intelligence and improve output and results.
Lower friction to adoption, because you can use the tools you already have and trust across multiple experiences.
Clear differentiation, where the Microsoft experience can better support agentic sales use cases and workflows, connecting CRM data, partner intelligence, and business context across Dynamics 365 Sales, Microsoft 365, and beyond.
MCP helps turn Dynamics 365 into an agent-powered engine for action
Data and sales intelligence are just the beginning. Because MCP is an open protocol, the same model that brings trusted data into your agents can connect them to nearly any external system or capability, from research and enrichment to workflow, analytics, and tools your teams have not even adopted yet. Today’s launch partners are a powerful starting point and as the MCP ecosystem grows, so does what your agents can do. This strengthens the broader Microsoft Copilot ecosystem and reinforces Microsoft’s agent extensibility.

Not just first-party agents
These partner MCP servers also work with any custom agent built in Copilot Studio, not only our first-party Dynamics 365 Sales agents. Customers can bring this same flexibility into the agents they build for their own specific workflows.

If you already subscribe to these solutions, this is immediate added value. Your existing subscription now flows directly into your agentic workflows in Dynamics 365 Sales, putting data and capabilities you already have to work inside the agent experience, with no duplicate integration or added licensing.

Announcing new MCP partners

ZoomInfo
ZoomInfo: Connect ZoomInfo’s verified business-to-business (B2B) data and context to Microsoft Copilot Studio via ZoomInfo’s headless go-to-market (GTM) context layer, GTM.ai. This surfaces 400M contacts, 100M companies, 120M direct dials, and billions of buying signals inside Microsoft Dynamics 365. In Dynamics 365 Sales agents, customers can enrich contact and account records inline with verified contacts, firmographics, technographics, funding history, and intent signals without manual entry or tab switching.

Dun & Bradstreet
Dun & Bradstreet: Anchored by the global standard D-U-N-S® Number identifier, the D&B Commercial Graph MCP server provides the foundational context layer that allows AI agents to understand business identity, relationships, and risk across the global economy, delivering outputs that are consistent, explainable, and auditable. Leverage the Commercial Graph in Copilot Studio to create custom agents and workflows across finance and credit, supply chain, compliance, risk, sales & marketing, and enterprise master data use cases.

LeadIQ
LeadIQ: LeadIQ connects directly into the Sales Qualification Agent, the same AI agent already researching and scoring every lead that enters Dynamics 365 Sales. Instead of bolting on a separate enrichment step, LeadIQ becomes a knowledge source inside that existing research flow: as the agent evaluates a lead, it calls LeadIQ for a verified work email and phone number, and the result lands in the lead’s Deeper insights alongside the agent’s other findings, cited, sourced, and ready before a seller ever opens the record. There’s no new tool to learn and no separate enrichment step to run. Verification just becomes part of your Dynamics 365 workflow.

Draup
Draup: Draup brings context-rich account and market intelligence into the Sales Qualification Agent—hiring surges, funding events, IT spend shifts, executive moves—then converts those buying signals into clear next actions. Every lead arrives researched, prioritized, and paired with a recommended play.

Gong
Gong: Bring Gong’s account and deal insights directly into the Dynamics 365 agent experience. With real-time customer insights like objections raised, risks flagged, or agreed-upon next steps right at sellers’ fingertips, GTM teams can execute on informed next-best actions.

Enlyft
Enlyft: Enlyft helps B2B technology vendors and their partners turn deep account intelligence—technology adoption, buying propensity, and competitive footprint into pipeline. Our MCP connector brings that intelligence into Dynamics 365 Sales agents, so a qualification agent reasons over a prospect’s real tech stack, competitive install base, and fit signals before a seller ever engages.

HG Insights
HG Insights. HG Insights extends Dynamics 365 Sales agents with trusted B2B market context through Model Context Protocol (MCP), giving sellers direct access to company intelligence—such as technology adoption, cloud and AI maturity, IT investment signals, firmographics, and market context—right inside the agent experience. By combining CRM data with this external market intelligence, Dynamics 365 Sales agents help reps prioritize accounts, uncover whitespace opportunities, and recommend more informed next actions throughout the sales cycle. HG Insights is trusted by 95% of Fortune 1000 B2B tech companies and every major hyperscaler to find, target, and convert their best opportunities faster, and this integration brings that same market intelligence to Dynamics 365 users.

These launch partners highlight how powerful and extensible Dynamics 365 Sales agents can become with MCP: more connected, more contextual, and easier to extend with the partner intelligence customers already trust. Customer can use parter MCP tools with Microsoft-built agents such as Sales Qualification Agent and Sales Opportunity Agent, or bring those same tools into custom agents built in Copilot Studio.

To get started, choose the sales scenario you want to improve, connect the right partner MCP tool, and define the insight or action the agent should support. Learn how to add custom research insights and MCP tools to Dynamics 365 Sales agents.

Want to become a partner? The MCP ecosystem on Copilot Studio is open and growing. Certify your MCP server to make your solution available to Dynamics 365 Sales customers.

The post Extending agentic Microsoft Dynamics 365 Sales with MCP appeared first on Microsoft Copilot Blog.

Inside Frontier Tuning

Frontier Tuning has three parts that work together: the environment where learning happens; the unique inputs you provide from your own business; and the tuned output models, skills, and harness that the system produces.

A continuously evolving environment. Tuning runs in a managed Reinforcement Learning Environment (RLE) used both for post-training and inference. During training, the system learns from real workflows, tool usage, and eval signals without affecting production systems. At inference it explores multiple frontier and fine-tuned models, from Microsoft AI and OpenAI, across turns to find stronger candidate paths before returning an answer. The system improves continuously as it learns from each interaction.

Your company’s data, domain knowledge, and workflows, in one platform. You bring your business data and know-how into the RLE: content, processes, conventions, terminology, and workflows that collectively define how your business runs. The experience is built to be easy to use, with no need for a data science degree. With a simple, guided approach, teams can bring data in and start tuning right away, enabling more people within your organization to capture the power of tuning.

Tuned models, skills, and harness that stay within your compliance boundary. This system produces tuned models, embeddings, skills, orchestration logic, and a runtime harness. All of this runs on your data, with your controls, without leaving your compliance boundary. The models inherit your access controls, so only people who could see the underlying data can access models built from it. The tools are virtualized, so agents can improve without affecting production systems.

Together, these three pieces form a loop that gets sharper with every agent interaction. As knowledge in your environment grows, the models and harness evolve with it, so your agents keep getting better at the work you actually do.

Fits the way you operate

Frontier Tuning fits into how you already build and operate agents. Users interact with agents tuned on your company’s data and workflows. Makers and developers build and refine these agents in the tools you’re already using, including Microsoft Copilot Studio and Microsoft Foundry.

For example, soon within Copilot Studio, you will be able to access the RLE and use data like transcripts, knowledge bases and Microsoft 365 artifacts to improve the agents you already rely on. We’re also bringing capabilities to Foundry to allow developers to tune agents alongside the tools you already use. Here too, you’ll be able to set up an RLE, bring in your data, and tune models, including Microsoft AI models, and runtime behavior. More details on Foundry support will come in the coming months. And today, Frontier Tuning is available in Private Preview through our Forward Deployed Engineering (FDE) team. FDEs can partner with you end to end: defining the scenario, setting eval criteria, running the tuning process and delivering the agent, all within your environment.

Whether you build in Copilot Studio, develop in Foundry, or partner with an FDE, Frontier Tuning fits how your business already operates.

Frontier Tuning in action

Frontier Tuning is already in the hands of customers. We’ve partnered with a focused set of organizations including Land O’Lakes, EY, Bristol Myers Squibb, Pearson, McKinsey, McCarthy Tétrault, and the Josh Bersin Company.

“Microsoft Frontier Tuning enabled us to generate significantly better Copilot outputs for Communication Coach. The results were more closely aligned with Pearson’s learning science, giving learners clearer, more actionable feedback on how to strengthen workplace communication,” said Gian Paolo Perrucci, Product & Technology Officer, Pearson.

“Microsoft Frontier Tuning is set to transform the tax practice across the global EY organization. By combining a tax-domain–tuned reasoning LLM with our extensive enterprise knowledge and insights from our Tax Advisors, EY is elevating the delivery of tax services. Leveraging client context in Microsoft Work IQ and deep EY expertise, we are tuning an advisory agent within the RLE that will be deployed to 75,000 tax professionals globally in the coming period.”

– Ben Ambrosino, EY Global Tax CTO, EY

“Microsoft Frontier Tuning has given us a powerful way to bring Galileo’s research-backed HR intelligence into bespoke agents inside the Copilot experience. It is one of the most compelling capabilities we have seen for putting deep domain expertise into the daily flow of work.”

– Josh Bersin, Founder and CEO, The Josh Bersin Company

“With Frontier Tuning, we’re teaching the system how Microsoft HR works – capturing organizational knowledge in one connected environment that learns and improves with every use. We partnered with our product teams until the results were undeniable; successful task completion increased from 13% to 87%. Now we’re expanding to more HR workflows.”

– Nathalie D’Hers, CVP Employee Experience

The pattern across these engagements is consistent: when you teach the system how your organization actually works, you get much higher fidelity output and more predictable execution.

Get started

If you’re interested in Frontier Tuning, visit aka.ms/frontiertuning to learn more. We will follow up with additional details.

The post Frontier Tuning: Teaching AI to work the way you do appeared first on Microsoft Copilot Blog.

Expectations for agents are changing quickly. Teams want to move beyond conversational experiences to systems that can help get work done by interacting with applications, executing workflows, collaborating across tools, and supporting customers more naturally across channels.

But getting there can be tough. Many organizations are still balancing modern, real-time AI experiences with older systems and processes that were never designed to work together. That can leave teams stuck maintaining brittle automations, disconnected processes, and rigid customer interactions that are difficult to evolve. New updates in Microsoft Copilot Studio focus on helping organizations achieve more connected, adaptive automation systems—structured where needed and adaptive where valuable.

Computer use and workflows: Adapt automation to your team’s real work

Traditional automation works best in predictable environments. But many real business processes are anything but predictable. Interfaces change. Vendor portals update unexpectedly. Legacy systems lack APIs entirely. As a result, even relatively simple processes can require constant maintenance just to keep automations running reliably.

That’s the kind of gap computer-using agents are designed to help close.

Computer-using agents are now generally available

With computer-using agents now generally available in Copilot Studio, organizations can build agents that interact directly with websites and desktop applications through the user interface (UI). This helps you automate processes that previously relied on brittle scripts or manual workarounds because the underlying systems lacked APIs.

With the new release also comes new enterprise-ready capabilities designed to help you operationalize UI automation more confidently. Organizations can now manage credentials more securely, choose models best suited for different automation scenarios, and build more resilient automations that can adapt to changing interfaces instead of breaking whenever a screen or webpage changes.

In addition, organizations can now embed computer-using agents directly into multi-step workflows. This feature, now moving into preview, further helps teams combine API-based actions, approvals, business logic, and adaptive UI interactions within the same automation system.

But adaptability automation still needs structure. As organizations scale beyond isolated automations, teams need a way to orchestrate all these in a way that’s easier to understand, maintain, and evolve over time.

That’s where the new workflows experience in Copilot Studio comes in.

A simpler, more intuitive way to build powerful workflows

Now available in early release environments, the redesigned workflows experience introduces a more intuitive visual designer for building and orchestrating agentic automation in one place. Instead of stitching together disconnected tools and logic across multiple surfaces, you can design workflows end-to-end on a unified canvas. This helps you more clearly see how actions, decisions, and AI-powered steps work together across a business process.

A core component of the new experience is the ability to add existing agents directly into workflows. These agent nodes allow you to create automated solutions that keep the scalable reliability of workflows while bringing in AI intelligence when you need it. For example, when a workflow hits a decision that can’t be captured in simple if-then logic—where it needs to use reasoning over context, orchestrate tools, or retrieve knowledge from multiple sources—an agent node can help bridge the gap and make your workflow more effective.

The new designer also helps reduce friction for teams building and maintaining these systems. Inline configuration, simplified building blocks, and node-level testing help validate workflow behavior earlier and iterate more quickly. In addition to agent nodes, AI-powered actions like classification, content generation, and decision support can now be incorporated directly into the workflow.

Together, these updates help organizations combine deterministic orchestration with adaptive execution—structured where needed, adaptive where valuable.

How Graebel combines flows and computer-using agents

Graebel, a global leader in talent mobility, processes thousands of employee relocation requests each year. Most of these come in as unstructured emails filled with unique instructions, attachments, and edge cases. Because Graebel’s proprietary Global Connect platform lacked API support, earlier automation efforts proved too rigid to keep up with the variability of real-world requests. That meant lots of manual input and handoffs—which automation was supposed to solve. Basically, Graebel needed automation that could use reasoning, not just click.

Working with GET AI and Microsoft, Graebel built the Graebel Service Order Agent in Copilot Studio using computer use capabilities to help automate the process end to end. The agent can interpret incoming emails, validate requests against business rules, operate Global Connect directly through the UI, and escalate exceptions through workflows when needed.

By adopting Microsoft Copilot Studio and AI agents, we’ve moved beyond traditional automation to a more intelligent, scalable operating model. This initiative strengthens our ability to serve clients faster and more accurately while positioning Graebel for long-term growth.

—Matt Brownlee, Chief Revenue Officer, Graebel

The Service Order Agent is live today and designed to scale across more than 30 relocation service categories. So far, results include a meaningful reduction in manual effort, faster service-order turnaround, more consistent data quality, and a repeatable blueprint for bringing intelligent automation to the rest of their operations.

Connect intelligent automation systems with Work IQ and interoperable agents

As automation systems become more adaptive, another challenge quickly emerges: connection. Even the most capable agent can only go so far if it operates in isolation. Many organizations are still navigating fragmented ecosystems where agents, workflows, APIs, and external tools all function separately. This naturally makes it difficult to share context or complete work across systems without custom integration effort.

This fragmentation—which is very common—slows adoption and makes it harder to scale intelligent automation beyond isolated pilots.

Now, new interoperability and extensibility capabilities in Work IQ help organizations build more connected agent systems—making it easier for agents, workflows, and enterprise tools to operate together across environments.

With the new Work IQ REST API and command-line interface (CLI) capabilities, teams can integrate Work IQ more flexibly into existing operational and development workflows. Support for remote model context protocol (MCP) servers also introduces a more standardized way to connect agents with tools, services, and enterprise resources. This reduces the need for one-off integrations across growing agent ecosystems.

And as organizations deploy more specialized agents across departments and business processes, coordination between those agents becomes increasingly important. With agent-to-agent (A2A) communication now generally available in Copilot Studio, agents can exchange information, delegate tasks, and be set up to work together more effectively across systems and workflows.

Together, these updates continue the shift from isolated AI experiences toward connected operational platforms—where workflows, agents, APIs, and enterprise systems can be designed to collaborate more naturally across the organization.

Learn more about these new Work IQ interoperability and extensibility updates.

Bring more natural, responsive experiences to customer voice interactions

For many organizations, voice support is still one of the most difficult channels to modernize. Customers get stuck in rigid phone trees, repeat information multiple times, or lose context entirely when they’re transferred to a live agent. Meanwhile, service teams are under pressure to handle growing call volumes without sacrificing customer experience.

Copilot Studio is helping organizations move beyond those limitations with real-time voice agents, now generally available in North America through Dynamics 365 Contact Center. These capabilities help organizations build more natural voice experiences that can identify callers, answer questions, take action during conversations, and transition customers to live agents while preserving context.

Support for speech-to-speech (S2S) voice experiences also makes it easier to connect voice agents into existing customer service and operational systems.

Now, as voice agents become part of real customer interactions, governance and operational readiness become increasingly important. A poor escalation experience, missing context during handoff, or lack of monitoring can quickly become a customer trust issue—not just a technical issue.

That’s why we’re also sharing a new in-depth voice agent governance guide. It covers practical considerations for scaling customer-facing and real-time voice agents responsibly, including escalation testing, monitoring, security, compliance, and operational readiness.

Learn more about real-time voice agents in Copilot Studio and explore the new governance guidance for customer-facing voice agents.

What else is new and improved in Copilot Studio

• A new orchestration layer in Copilot Studio improves how agents execute business processes with greater accuracy and efficiency. Built on an upgraded AI stack, it has demonstrated measurable gains—improving evaluation performance by approximately 20% while decreasing net token usage by 50%—so agents can complete tasks more reliably and cost-effectively.¹ By strengthening tool orchestration and execution quality, the new orchestrator helps ensure more consistent outcomes across complex, multi-step business processes. The result is faster, more dependable automation that scales across enterprise scenarios. This feature is currently in early release environments, where it applies automatically.
• Agent lifecycle visibility updates help the whole team understand an agent’s approval and publishing status. Agent creators can more easily understand whether an agent is still generating, ready for testing, successfully published, or encountering issues, which reduces guesswork during development and iteration. For IT and platform teams managing agents across environments, clearer publishing and status visibility can make it easier to identify stalled deployments, troubleshoot operational issues, and maintain better oversight as agent programs scale.

All together, these updates are focused on helping teams solve the kinds of problems that slow automation efforts down in the real world: workflows that break when systems change, disconnected tools that create extra manual work, and customer experiences that still feel rigid or fragmented.

With new investments across computer-using agents, workflows, interoperability, and real-time voice, Copilot Studio continues to expand as the agentic platform for building agents, apps, and workflows. The goal is simple: help organizations build systems that are easier to connect, easier to adapt, and easier to operate at scale—without losing the structure, visibility, and governance enterprise teams depend on.

Stay up to date on all things Copilot Studio

More is coming across voice channels, workflows, and the building experience. Check out all the updates as we ship them, as well as new features releasing in the next few months here: What’s new in Microsoft Copilot Studio.

To learn more about Microsoft Copilot Studio and how it can transform productivity within your organization, visit the Copilot Studio website or sign up for our free trial today.

Take your automation further

Design adaptive AI systems that integrate across tools and workflows to help teams get meaningful work done.

Try Copilot Studio today

¹ Source: Microsoft usage data, 2026.

The post New and improved: Computer-using agents, a new workflows experience, and real-time voice experiences appeared first on Microsoft Copilot Blog.

Governance built into the foundation of your agent program is what separates a successful production deployment from one that stalls—or fails publicly. This guide explains how to design, manage, and scale customer-facing, real-time voice agents using Microsoft Copilot Studio, with a focus on governance, reliability, and enterprise readiness.

Imagine a customer calling your contact center about a billing dispute. A real-time voice agent answers, identifies the customer, references their account history, resolves the issue, and—when needed—hands off to a live agent with full context preserved. Human agents focus on exceptions, not routine queries.

Now imagine that same scenario without agent governance. The agent was built, published directly to production, and never tested for escalation. Monitoring was not enabled. The first signal of a problem is a customer complaint—or a data exposure.

Customer-facing agents are becoming the front door for how organizations engage with customers, handling intent and outcomes across conversational AI experiences. What began as chat has evolved into always-on agents that resolve issues, take action, and now support real-time voice across digital and contact center environments using platforms like Copilot Studio. The opportunity is massive—but so is the cost of getting the foundation wrong. Just as self-service and Q&A agents redefined support at scale, this shift will fundamentally reshape how companies operate.

Why real-time voice agents require a different governance lens

Most organizations already govern internal AI tools designed for known users and controlled environments. Customer-facing agents operate under fundamentally different conditions. There are unknown users, public channels, brand exposure, and direct access to customer data and downstream systems. Failures in these customer experience events mean operational, regulatory, and reputational consequences.

This is why governance cannot be treated as a final approval step. As real-time voice agents scale, governance must be built into how they are designed, deployed, monitored, and evolved from the start. Organizations that treat governance as an accelerant—rather than a constraint—can move faster and more confidently than those who bolt it on later.

Principle: Governance as a design principle can streamline approval, which leads to accelerated scale and adoption.

Why real-time voice agents raise the stakes

Text‑based agents require governance, but real‑time voice introduces stricter operational constraints. Latency budgets are tighter, failures are immediately apparent to customers, and interruption handling, turn‑taking, session state, and escalation behavior directly affect service reliability.

Voice agents are typically deployed in high‑impact scenarios such as billing, orders, and service disruptions, where they integrate with Dynamics 365 Contact Center workflows. In these environments, agents must identify callers, reference active cases, execute actions, and escalate predictably.

For real‑time voice, escalation is a first‑class system requirement. Handoffs to human agents must preserve full conversational context and session state, and be validated under load before production traffic is routed.

Model selection also becomes operationally significant. Copilot Studio real‑time voice agents use purpose‑fit models to balance latency, quality, and reliability while remaining governed through a centralized control plane.

What good looks like: A production voice agent deployment has been tested for escalation behavior, latency under load, and handoff context preservation before any customer traffic is routed to it. Monitoring is active from day one, not added after the first incident.

A governance framework for the full agent lifecycle

Governing customer-facing agents effectively requires capabilities that span the full agent lifecycle. This is especially critical for business-to-consumer (B2C) agents, which operate in always-on, customer-facing contexts and must handle real-time interactions, actions, and sensitive data at scale—particularly in high‑stakes modalities like voice.

Copilot Studio provides this governance as a managed agent platform, enforcing controls through managed operations and managed security across the full lifecycle. That goes from build access and data connectivity to release, monitoring, and auditability. Rather than relying on documentation or custom wiring, governance is centralized in the Microsoft Power Platform control plane and consistently applied across chat, voice, and contact center scenarios.

The following five‑stage governance framework reflects how managed capabilities come together across the full lifecycle of customer-facing agents:

1. Govern the builder
2. Govern the build
3. Govern the release
4. Govern the runtime
5. Govern the lifecycle

Stage 1: Govern the builder

Before a single topic is created, agent governance starts with who is allowed to build and what they are allowed to connect.

• Define builder roles and environments. Specify who can create agents and which environments they can work in, using role‑based access in the Power Platform admin center.
• Set data access boundaries early. Apply data loss prevention (DLP) policies before development to determine which connectors and data sources agents can use.
• Maintain environment separation. Use distinct development, test, and production environments to validate changes before deploying them to customer‑facing scenarios.
• Standardize on managed solutions. Package agents in managed solutions to support versioning, controlled promotion, and rollback across environments.

What good looks like: A new agent builder requests access and is provisioned into a dedicated development environment. DLP policies are pre-applied. They cannot publish to any customer-facing channel without an administrator approval step.

Stage 2: Govern the build

How an agent is built determines how safe and predictable it is in production.

• Configure authentication by channel. Decide whether sessions are authenticated (Microsoft Entra ID or supported identity provider [IdP]) or anonymous, and design data access accordingly. (For public-facing scenarios like 800 numbers and public websites, anonymous real-time voice sessions are common.)
• Set generative AI behavior explicitly. Define and check grounding, topic scope, and allowed behaviors rather than relying on default settings.
• Validate escalation paths. Test and verify handoff to live agents with full conversation context preserved for all voice scenarios.
• Apply content moderation intentionally. Define clear engagement boundaries, enforce agent governance and policy controls, and rigorously red‑team and validate edge cases before deploying to production.

What good looks like: Testing escalation paths before publishing an agent to a customer-facing channel, so you can go live with more confidence. Catching errors before the first live escalation is critical to creating a good customer experience.

Stage 3: Govern the release

Moving an agent from development to production requires controlled, auditable steps.

• Standardize promotion paths. Promote agents through dev, test, and production using managed solutions and Power Platform pipelines with an auditable change history.
• Apply pre‑production validation gates. Require checks for conversation quality, escalation behavior, latency under load, and data access before publishing.
• Plan and test rollback. Define and validate rollback procedures for production issues prior to go‑live.
• Separate publish authorization. Require explicit approval to publish agents to customer‑facing channels, independent of build permissions.

What good looks like: An agent must pass a defined pre-production checklist and receive administrator approval to publish before any customer traffic reaches it. Every version promotion is tracked in the solution history.

Stage 4: Govern the runtime

Once an agent is live, governance shifts from control to visibility and response.

• Enable runtime observability. Turn on conversation transcripts and analytics in Copilot Studio before routing customer traffic.
• Define operational thresholds. Monitor metrics such as escalation rate, resolution rate, latency, and session completion, with alerts for deviations.
• Establish incident response. Define processes for detecting, triaging, and mitigating production issues in voice agents integrated with Dynamics 365 Contact Center.
• Monitor usage and capacity. Track session volume, message usage, and capacity limits to support scaling and stability.

What good looks like: Early detection through active monitoring. Voice agents that interact with customers without active monitoring are operating without a safety net. Issues that could persist for hours without analytics can be caught in minutes with these guards in place.

Stage 5: Govern the lifecycle

Voice agents are not static. They evolve as scenarios expand, customer needs change, and the platform advances. Managing change safely is as important as the initial deployment.

• Version agent configuration. Track changes to topics, actions, authentication, and generative AI settings using application lifecycle management (ALM) and source control.
• Validate changes pre‑production. Test all updates in non‑production environments to avoid regressions in core scenarios, including voice flows and escalation behavior.
• Coordinate releases operationally. Communicate deployment windows to IT and contact center operations teams.
• Evolve governance as scale grows. Reassess role-based access control (RBAC), DLP policies, environment strategy, and publishing permissions as agent count and channel coverage expand.

Platform capabilities that support agent governance

Copilot Studio provides a centralized control plane for building, operating, and governing customer‑facing agents. The platform capabilities below directly enable the governance framework described above and should be configured before scaling B2C deployments:

• Power Platform admin center: Central governance surface for environments, DLP policies, user access, and capacity management; the primary enforcement layer for agent governance.
• Environment management: Separate development, test, and production environments to support validation and controlled promotion of customer‑facing agents.
• Data loss prevention (DLP) policies: Environment‑level connector controls that define which data sources and services agents can access before any connections are established.
• Managed solutions and Power Platform pipelines: Package agents as managed solutions and promote them through environments with version tracking, rollback support, and an auditable change history.
• Microsoft Entra ID and channel authentication: Configure customer‑facing authentication using Entra ID or supported identity providers to enable secure, scoped access to customer data.
• Generative AI controls and content moderation: Per‑agent configuration for grounding, topic scope, allowed behaviors, and content filtering, applied deliberately prior to public deployment.
• Conversation transcripts and analytics: Built‑in logging and analytics providing runtime visibility into agent behavior, escalation patterns, and coverage gaps.
• Dynamics 365 Contact Center integration: Native escalation to live agents with case context preservation and unified conversation history for voice deployments.
• Azure Speech: Underlying speech infrastructure for real‑time voice agents, with implications for latency, reliability, and capacity planning.
• Dataverse security model: Row‑level and business‑unit security controls governing agent access to customer records in Dynamics‑integrated scenarios.

Security, privacy, and compliance for customer-facing agents

For IT and security teams, governance of customer-facing agents must also address data handling, regulatory requirements, and audit readiness. These are not secondary concerns—they’re often the first gate any enterprise B2C deployment must pass through.

Customer data and PII in voice interactions

Real-time voice agents generate conversation transcripts that may contain personally identifiable information. Establish clear retention policies for these transcripts before deployment. Define who has access to conversation logs, how long they are retained, and whether they are subject to deletion requests under applicable privacy regulations.

Regulatory considerations

Depending on your industry and geography, customer-facing AI agents may be subject to requirements under General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or sector-specific regulations in financial services or healthcare. Review applicable requirements with your legal and compliance teams before deploying agents to regulated customer scenarios. DLP policies in the Power Platform admin center are a key compliance control.

Audit logging and compliance evidence

Power Platform and Copilot Studio support audit logging through Microsoft Purview and the Power Platform admin center. Ensure audit logging is enabled before production deployment and that logs are retained according to your organization’s compliance requirements.

Credential and secret management

Agents that connect to external systems require credentials and connection strings. Do not store secrets in agent configuration directly. Use environment variables in Power Platform or Azure Key Vault references to manage credentials securely, with access controlled through role assignments.

Note for architects: Security and compliance review should be a gate in Stage 3 (govern the release), not an afterthought discovered during audit. Engage your security and compliance teams in the pre-production validation checklist.

Five anti-patterns that derail production AI deployments

Organizations that have scaled B2C agents successfully tend to have avoided the same set of avoidable mistakes. These are the patterns most likely to cause problems once customer traffic is live.

1. Skipping environment separation: Building and publishing agents in the same environment, or directly in production, allows untested changes to reach customers and is one of the most common causes of early deployment issues.
2. Publishing voice agents without tested escalation: Escalation to a live agent is a core part of voice agent design. Untested handoff paths that fail to preserve customer context degrade the experience more than having no agent at all.
3. Granting broad DLP exceptions under schedule pressure: Temporarily relaxing DLP policies often becomes permanent, introducing data access risk and audit gaps that are difficult to remediate later.
4. Treating monitoring as a post‑launch activity: When transcripts, analytics, and alerts are not enabled before go‑live, production issues surface through customer complaints rather than operational signals.
5. Building open‑ended agents without defined scope: Broad, general‑purpose agents are harder to test, govern, and improve than agents scoped to specific customer scenarios with clear success criteria.

How to operationalize voice agents

As teams move from pilots to production, a small set of patterns consistently differentiates voice agent deployments that scale.

• Start with well‑defined customer scenarios rather than broad open‑ended agents. Clear scope simplifies risk assessment, testing, and measurement. A voice agent designed for order status or billing inquiries is easier to govern and iterate on than one intended to answer arbitrary customer questions.
• Treat real‑time voice as an extension of existing digital agent governance, not an exception. Teams that have already governed chat‑based agents in Copilot Studio are well positioned to apply the same controls to voice, while accounting for stricter latency, escalation, and runtime requirements.
• Design escalation as a primary flow, not a fallback. Agents integrated with Dynamics 365 Contact Center should preserve full conversational and case context on handoff. Predictable escalation maintains continuity; dropped context undermines trust.
• As programs scale, three governance questions remain central:
  • Which customer scenarios are appropriate for automation versus human handling?
  • Where does real‑time voice materially improve the experience versus add operational complexity?
  • How quickly can production issues be detected and resolved once agents are live?

Using Copilot Studio as a governance foundation for agents

Copilot Studio and Power Platform provide a centralized environment for building, operating, and governing agents, which becomes increasingly important as deployments expand from internal use cases to customer‑facing channels.

Establish governance once in Copilot Studio, and scale it across chat, voice, and backend‑driven agents without fragmentation. As a centralized control plane, the platform helps you enforce consistent policies and maintain operational oversight as agents expand across channels, regions, and customer scenarios.

For organizations already using Copilot Studio, many of the governance capabilities described here are available today. Support for real-time voice agents in Copilot Studio is now generally available in North America, with deployments delivered first through Dynamics 365 Contact Center. Language support, additional regions, and broader publishing channels will expand over time as part of Copilot Studio’s ongoing roadmap.

Learn more in the announcement blog for real-time voice agents.

Governance readiness checklist for customer-facing voice agents

Before deploying a customer-facing or real-time voice agent to production, verify governance readiness across these core dimensions.

Access and environment

• Separate development, test, and production environments are provisioned
• Role-based access is configured—developers cannot publish directly to production
• Advanced connector policy is applied to all environments before development begins
• Publishing permissions for customer-facing channels require administrator approval

Build and configuration

• Authentication and identity are configured appropriately for the channel (authenticated or anonymous)
• Generative AI settings, grounding, and content moderation are configured deliberately
• Credential and secret management uses environment variables or Azure Key Vault references
• The agent is packaged in a managed solution with tracked versioning

Testing and release

• Escalation paths to live agents have been tested with context preservation verified
• Latency and behavior have been validated under simulated load
• A pre-production validation checklist has been completed and signed off
• A rollback procedure has been defined and tested
• Audit logging is enabled and log retention meets compliance requirements

Runtime and operations

• Conversation transcripts and analytics are active before first customer interaction
• Operational thresholds (escalation rate, session completion rate) are defined with alerts
• An incident response procedure is defined and communicated to operations teams
• Usage monitoring is in place for capacity planning
• A change management process is defined for updating live agents

Getting started with customer-facing agents

Organizations ready to operationalize B2C agents should begin with the following steps:

• Align on priority scenarios. Agree on customer scenarios, scope, success criteria, and escalation requirements before any development begins.
• Set up environments and governance. Configure separate dev, test, and production environments and apply DLP policies before granting developer access. Define role‑based access and require administrator approval for publishing to customer‑facing channels.
• Engage security and compliance early. Review applicable regulatory requirements and establish data retention policies for conversation transcripts.
• Build and validate deliberately. Start with a scoped agent, use managed solutions, and be sure to test and verify escalation paths.
• Confirm readiness before go‑live. Complete the governance readiness checklist and enable monitoring and escalation thresholds prior to routing customer traffic.

With the right foundation in place, teams can scale customer‑facing and real‑time voice agents—while maintaining the reliability, security, and operational integrity IT teams are responsible for protecting.

Resources for governing AI agents

• An overview of real-time voice agents in Copilot Studio
• Extend AI voice support: Introducing real-time voice agents in Microsoft Copilot Studio
• Power Platform admin center documentation
• Dynamics 365 Contact Center documentation

Governance starts early

Establish a governance foundation with Copilot Studio that scales across chat, voice, and backend-driven agents.

Try Copilot Studio today

The post The in-depth guide to managing real-time voice agents at scale appeared first on Microsoft Copilot Blog.

As organizations scale their use of AI agents, IT teams face a familiar challenge: how do you expand automation without losing control? Individual agents can be powerful, but as they connect through workflows and integrate across systems, requirements for visibility, governance, and predictability become much more complex. And capability must be grounded in confidence.

The April 2026 updates in Microsoft Copilot Studio focus on building that confidence across the platform. From increasing visibility and governance for admins to expanding intelligent workflow capabilities, these features help you move from isolated automation to connected, reliable systems.

Build and scale agents with better visibility and control

As agents expand across organizations and business processes, admins need clear visibility into how they’re performing, how they’re secured, and what they’ll cost to run. These updates help you manage agents more effectively without adding more friction—or risk.

See agent performance and status more clearly

Copilot Studio now surfaces agent status directly in the authoring experience, giving you immediate insight into each agent’s security and protection posture. You can quickly identify issues like authentication gaps or policy impacts and investigate them at the source. This helps reduce guesswork and speed up resolution.

As you gain clearer visibility into agent performance, you can also share those insights more safely. The Analytics Viewer role, now generally available, introduces read-only access to an agent’s Analytics page.

The Analytics Viewer role allows us to provide meaningful performance insights to business and operational stakeholders while maintaining strict production governance. It cleanly separates operational visibility from agent configuration and publishing rights.

—Mohamed Arhab, Solution Architect, City of Montreal

Allowing analysts and stakeholders to monitor performance, without giving them the ability to modify the agent, helps resolve a long-standing tradeoff between visibility and control. Now it’s easier to share insights broadly while maintaining clear separation of responsibilities.

Speaking of extending visibility and control, there’s more good news: Microsoft Agent 365 is now generally available. Agent 365 is the centralized control plane for managing agents across your environment. This brings together visibility into agent inventory, permissions, behavior, and activity in one place so that you can monitor and govern agents consistently, not just where they’re built.

For Copilot Studio customers, this means the agents you create can be managed alongside agents from Microsoft 365 and partner ecosystems, with shared policies, security controls, and lifecycle oversight. As Agent 365 continues to expand its integrations and multi-agent capabilities, it further strengthens Copilot Studio’s role as the place where agents are built—while governance scales across the full system. Learn more about Agent 365.

Plan and scale with clearer cost visibility

The expanded agent usage estimator now includes Dynamics 365 agents, such as Sales Qualification Agent and Customer Service Agent. By forecasting Copilot credit usage across both Copilot Studio and Dynamics 365 scenarios in one place, you can model usage more accurately and scale deployments—helping avoid unexpected cost surprises.

With these recent admin updates, the result is fewer bottlenecks, better-informed decisions, and a clearer path to scaling agents across your organization.

Expand workflows into intelligent, governed automation systems

In Copilot Studio, workflows are step-by-step automation processes that complete actions or tasks in a deterministic, reliable way. As workflows become the backbone of business automation, these new updates help you extend their capabilities—bringing in more AI-powered reasoning, centralized governance, and a growing ecosystem of tools in a way that’s reliable and secure by design.

Design and validate workflows with more clarity

One powerful way to make your workflows more adaptable and effective is by embedding Copilot Studio agents directly into them. Using agent nodes inside workflows means that instead of just performing the task with rigid logic, the workflow can delegate reasoning, decisions, or output generation to an agent at any prescribed step of the process.

This makes workflows more resilient to real-world situations—which have a lot of variability—while still following the defined structure that make IT teams less nervous.

In addition to embedding agents, you can now also add and configure AI actions directly within the flow to understand requests, route work, and generate content dynamically. And with the ability to test individual steps using sample inputs, teams can validate behavior earlier, debug more effectively, and refine workflows before they’re deployed.

In practice: Unifi, North America’s largest provider of aviation ground handling services, used Copilot Studio and Power Platform to automate legal contract review by combining agents with deterministic workflows. Instead of relying on a single agent, they broke the process into coordinated steps that extract, classify, and validate key terms across documents. This system reduced contract processing from days to minutes and delivers the same level of performance as much more expensive, off-the-shelf products built specifically for the legal industry.

The result is a workflow experience that’s more adaptable and more predictable to operate. This helps give teams—both makers and administrators—more confidence in creating more sophisticated automation that doesn’t sacrifice clarity or control.

Scale workflows across systems with built-in governance

Speaking of clarity and control, there are also new updates to workflows that help you scale automation without introducing new governance risks.

Workflows can now connect to a broader ecosystem of tools, including model context protocol (MCP) server-enabled tools (preview), which makes it easier to take action across systems while staying within Microsoft security, permission, and compliance boundaries. This allows workflows to execute tasks and involve users for review and approval within governed processes.

We’ve also introduced a centralized, admin-controlled environment for Workflows Agent. This makes it easier to apply data loss prevention (DLP) policies consistently and maintain visibility across automation, so workflows remain compliant by design, even as they scale.

Together, these updates make it easier to move from isolated automations to connected, intelligent systems. With those systems, you can scale workflows across your organization with greater confidence, control, and flexibility.

Bring business apps directly into your agents

As agents become part of everyday work, a common gap emerges: they can generate insight, but acting on that insight often requires switching tools, re-creating context, or handing work off across systems. Support for apps in agents, now generally available, helps to close that gap.

Turn intent into action inside Copilot Chat

Agents built in Copilot Studio can now surface rich, interactive app experiences directly in Copilot Chat, allowing users to review data, update records, approve requests, or create assets in place. Instead of switching tools or re-creating context, work happens seamlessly within the flow of conversation. This helps reduce friction and empowers teams to move faster from insight to execution.

Work across the systems your business already runs on

Apps in agents bring together Microsoft and partner applications—from Power Apps to Dynamics 365 and beyond—so agents can take action across the systems your teams already use. These experiences are built and orchestrated in Copilot Studio, where you define how agents interact with apps, data, and workflows to support real business processes.

Extend and scale with trusted integrations

Through the Agent Store, you can adopt ready-made agent experiences or extend your own with partner-built integrations—while maintaining enterprise-grade security, permissions, and admin control. Options include:

• Adobe Express (seen above)
• Box
• Figma
• Monday.com
• Wix

These options (and more) make it easier to scale agent usage across your organization without losing oversight.

These capabilities, all generally available now, help teams shift agents from being informational tools to operational ones. They bring real business actions into Copilot Studio agents in a way that’s both more functional for users and manageable for IT—helping teams complete work efficiently while maintaining the governance needed to scale.

Learn more about apps in agents.

What else is new and improved in Copilot Studio

• Evaluation insights and automation updates now make it easier to generate test cases from analytics, simulate multi-turn interactions, and automate evaluations through APIs and connectors. You can turn real user conversations into targeted test sets, better reflect complex, real-world scenarios, and run evaluations programmatically. Together, these capabilities help you operationalize agent quality and maintain confidence as you scale.
• Custom metrics for outcome-based measurement help you track what actually matters to your business, not just usage. Define success in your own terms—like resolution rates or conversions—and automatically evaluate conversations against those outcomes, making it easier to understand impact, align stakeholders, and make data-driven decisions.
• Work IQ API is now available in public preview to bring Copilot’s intelligence layer—grounded in organizational context, memory, and signals—into your own agents and workflows. With built-in orchestration and enterprise-grade security, you can build agents that understand what’s happening across your business without managing raw data or complex integrations.
• Agent-to-agent (A2A) communication is now supported in Work IQ, allowing agents to collaborate as peers and delegate tasks using shared organizational context. This makes it easier to build multi-agent systems that can coordinate work, maintain context across interactions, and deliver more grounded, role-aware outcomes.
• GPT-5.5 Thinking is now available in Copilot Studio early release cycle environments as GPT-5.5 Reasoning, further expanding model choice with its more advanced analysis capabilities. This model is also rolling out across Microsoft 365 Copilot in Copilot Chat, Word, Excel, and PowerPoint.

Stay up to date on all things Copilot Studio

More is coming across voice channels, workflows, and the building experience. Check out all the updates as we ship them, as well as new features releasing in the next few months here: What’s new in Microsoft Copilot Studio.

To learn more about Microsoft Copilot Studio and how it can transform productivity within your organization, visit the Copilot Studio website or sign up for our free trial today.

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The post New and improved: Agent governance, intelligent workflows, and connected app experiences appeared first on Microsoft Copilot Blog.

That’s why we’re excited to announce the general availability of real‑time voice agents in Microsoft Copilot Studio launching in Dynamics 365 Contact Center. These agents are designed for nuanced, high‑impact interactions where voice experiences need to adapt in the moment—while still operating within trusted, enterprise‑grade solutions.

Real-time voice agents build on the momentum of Copilot Studio as a proven, enterprise-scale platform. Over 80% of Fortune 500 companies now have active agents built using our low-code/no-code tools, creating a strong foundation for bringing real-time, conversational voice experiences into their customer workflows.¹ This widespread adoption shows how ready organizations are to extend their existing Copilot-powered agents into natural, responsive voice interactions.

Why AI voice support needs to go off script

For decades, menu‑based interactive voice response (IVR) systems provided predictability, reliability, and compliance at scale. Over time, organizations layered in speech recognition and automation to reduce friction and manage growing call volumes more efficiently. These approaches remain critical today and continue to power successful customer service operations across industries.

What’s changed is not the importance of voice, but the expectations customers now bring into voice interactions. Conversations rarely follow a straight line. Customers interrupt, clarify, change direction mid‑call, or introduce urgency without warning. When that happens, rigid interaction models can struggle to keep up, even when the underlying systems are reliable.

Meanwhile, across industries, contact centers are under pressure to do more with less. Interaction volumes continue to rise, margins are tighter, and customer expectations are shaped by digital experiences that feel fast, personal, and responsive. Many teams are already exploring AI through chatbots, voice automation, or workflow tools, but scaling those experiments into production voice experiences that customers trust is far harder than running a pilot.

Voice, in particular, exposes gaps immediately. Latency, awkward handoffs, or missing context are noticed in real time, often at the most critical moments. That’s why simply adding automation isn’t enough. As organizations move toward agentic, AI‑first service models, voice needs to work as part of a unified service layer: one where understanding, reasoning, and action happen together, and where context carries forward if escalation is required.

Meeting this bar doesn’t require replacing the voice systems that already work. It requires extending them with capabilities designed specifically for live, conversational interactions. This makes it possible to move beyond scripted interactions without treating voice as an isolated AI experiment.

Meet real-time voice agents for AI voice support

Real‑time voice agents represent a new premium mode within voice agents that sits under the broader category of conversational AI. They are optimized for low‑latency, interruptible, speech‑to‑speech conversations with real‑time reasoning. This distinction helps teams choose the right interaction model for each scenario without treating all voice interactions as equal.

These agents can move from intent to action to confirmation within a single interaction. They can retrieve or update information mid‑conversation and take action as the interaction unfolds. Customers can get faster resolution, while service teams can maintain consistent experiences and centralized operational control. This also frees human agents to focus their time and energy on conversations where judgment and empathy matter most.

High-volume self-service, designed for everyday voice interactions

Real-time voice agents are built for the high volume, business-to-consumer (B2C) interactions that define customer service at scale. These everyday inbound calls make up the majority of customer engagement across industries. To support this breadth, Copilot Studio enables organizations to grow their voice strategy—starting with deterministic, template-driven flows and expanding into dynamic, real-time voice agents as needs evolve.

Copilot Studio provides a documented set of external voice agent templates designed for unauthenticated, customer-facing interactions across both Copilot Studio and Dynamics 365 Contact Center, covering many of the core workflows customer service teams handle today, including:

• Billing and payments, which are among the most frequent and sensitive contact center interactions. Customers want clarity and resolution in the same call, not a handoff or follow-up. These scenarios often start with deterministic flows—confirming identity, checking balances, or processing payments—but can switch to dynamic, real-time voice agents that explain charges, respond to questions, and adapt tone as situations become more urgent.
• Order and reservation support across retail, travel, and hospitality, which often requires more dynamic handling. What begins as a simple status check can quickly shift into a change request or issue resolution. Real-time voice agents adapt to these pivots by grounding responses in live order or reservation data. They’re designed to act while preserving relevant context, supporting organizations as they evolve from structured flows to more flexible conversational automation.
• Eligibility and verification scenarios in healthcare, financial services, telecom, and the public sector, which rely on accuracy and trust. Deterministic steps—collecting required information, confirming eligibility criteria—can be paired with dynamic voice capabilities that answer questions as they arise and help preserve continuity if escalation or additional support is needed.
• Appointment scheduling and changes often involve interruptions and evolving preferences. Organizations can begin with predictable scheduling flows and grow into dynamic, real-time voice agents that let customers book, reschedule, or confirm details conversationally, without unnecessary restarting or repeating information as needs shift.
• Account and membership management, which often spans multiple tasks, from updating personal details to managing subscriptions or reviewing benefits. Deterministic updates can be combined with dynamic, context-aware voice interactions that stay connected to live account data, keeping these conversations efficient, accurate, and natural from start to finish.

From conversation to resolution, without breaking flow

Real‑time voice agents are built for real customer service environments, where escalation is a natural part of resolution rather than a failure of automation. At launch, these experiences are delivered through Dynamics 365 Contact Center, with conversation context carrying forward automatically, helping reduce the need for customers to restate information when human judgement is required.

As part of the Copilot Studio product roadmap, real‑time voice agents will also extend to Microsoft Teams Phone and additional Copilot Studio digital apps and channels, enabling organizations to bring consistent, context‑aware voice experiences to more customer touchpoints over time.

Voice automation designed for trust, control, and evolution at scale

For IT teams, voice automation has always been high impact but high risk. Feedback from early internal deployments reinforces the importance of pairing conversational intelligence with enterprise‑grade governance and lifecycle controls.

Innovation in voice does not require giving up control or predictability. Voice is a high‑stakes interaction surface, and customers notice immediately when experiences feel unreliable or inconsistent.

Copilot Studio takes a deliberate approach to real‑time voice by selecting the right models for the right moments, including the latest frontier models, optimized for the right balance of quality, latency, and reliability, without placing that complexity on customers. Built on Microsoft’s enterprise foundations for security, governance, and operational oversight, real‑time voice agents help organizations innovate with confidence while preserving trust.

Get started with Copilot Studio

Support for real-time voice agents is now generally available in North America for Dynamics 365 Contact Center, with language support, additional regions, and broader customer touchpoints expanding over time as part of Copilot Studio’s global rollout.

Learn more about real-time voice agents and sign back in to Copilot Studio to start scaling customer support with agents today.

New to Copilot Studio? Discover how you can transform your business by building, evaluating, managing, and scaling custom AI agents—all in one place. Sign up for a free trial of Copilot Studio today.

Build voice agents that adapt

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¹ Source: Microsoft usage data, 2026.

The post Extend AI voice support: Introducing real-time voice agents in Microsoft Copilot Studio appeared first on Microsoft Copilot Blog.

Microsoft Copilot Studio helps organizations move beyond isolated AI experiences and build connected systems of agents that can scale, adapt, and deliver real business value. Recent enhancements focus on making it easier for agents to work together across tools and data sources, while giving makers more control over how those agents behave in production.

What you’ll see this month: New generally available capabilities for multi-agent coordination across Microsoft Fabric, the Microsoft 365 Agents SDK, and open Agent-to-Agent (A2A) protocols—all of which help agents collaborate across your ecosystem and perform more valuable work. Plus, you’ll find updates to prompt authoring, model choice, and governance controls that can help make it faster to build and refine high-quality agent experiences with confidence.

Agents that work together across your entire ecosystem

The challenge in scaling AI inside an organization isn’t creating a useful agent. It’s about getting many agents—across teams and tools—to work together in a way that’s reliable and repeatable.

In many organizations, data teams might build one kind of agent, app teams another, and productivity teams yet another. Each agent can be valuable on its own, but once a workflow needs knowledge from one system, reasoning from another, and action in a third—teams often run into brittle handoffs and custom integration work. This slows agent adoption and makes it harder to move from promising pilots to real business impact.

This month, Copilot Studio takes a meaningful step forward: several multi-agent capabilities are rolling out to general availability over the next few weeks, giving your teams new ways to connect and orchestrate agents across your ecosystem. These updates include Microsoft Fabric integration, Microsoft 365 Agents SDK orchestration, and Agent-to-Agent (A2A) communication—all designed to help your agents operate together as a coordinated system rather than in isolated silos.

Multi-agent support for Microsoft Fabric

With multi-agent support, your Copilot Studio agents can work with Fabric agents to reason over enterprise data and analytics at scale. That means you can connect business-facing agent experiences more directly to the data estate they already rely on, without treating every data-intensive scenario like a one-off engineering project. Instead of working with limited or disconnected data, these agents will be able to operate with full business context—helping make their outputs more accurate, relevant, and actionable.

Multi-agent support for the Microsoft 365 Agents SDK

Using the Microsoft 365 Agents SDK, teams can now orchestrate Copilot Studio agents alongside agents built for Microsoft 365 experiences. Instead of recreating the same logic across multiple agents (think retrieving data, applying business rules, or completing common tasks), you’ll be able to reuse and combine existing capabilities. This makes it easier to compose cross-app workflows from what’s already been built, reducing duplication and keeping experiences more efficient and consistent.

Agent-to-Agent (A2A) support

With A2A support, Copilot Studio agents can directly communicate with and delegate work to other agents—first-party, second-party, or third-party—using an open protocol that allows universal access. This matters because the future of enterprise AI will not belong to a single stack. Organizations need to build agents on platforms that can participate in a broader ecosystem, not just operate within one product boundary. Copilot Studio A2A provides that interoperability and power.

The impact of multi-agent systems

We’ve already seen the power of this approach with the Ask Microsoft web agent, one of our early “customer zero” implementations. As site traffic and knowledge sources grew, the single-agent architecture began to strain, creating slower response times. Using Copilot Studio, the team upgraded the agent to a modern architecture with generative orchestration and multi-agent coordination.

Now, multiple sub-agents handle different parts of the site—Microsoft Azure, Microsoft 365, pricing, trials, and more—while the main agent orchestrates them to provide fast, coherent, multi-turn responses. This setup allows Ask Microsoft to answer complex questions involving multiple products or services, and to tailor responses based on where the customer is on the site.

Building a more advanced assistant with Copilot Studio has meaningfully raised the bar for our customer experience and enabled us to scale faster across products to deliver real business impact.

—Alyse Muttera, Director of eCommerce Programs at Microsoft

To show how this approach works in other organizations, consider a common scenario at a bank. The loan department has one agent handling mortgage applications, while the banking department runs a separate agent for account inquiries. A customer, however, expects a single seamless experience.

Multi-agent orchestration lets each specialized agent manage its area of expertise while coordinating responses behind the scenes. For instance, if a customer asks about a mortgage payment and their account balance in the same interaction, the system delivers a cohesive, context-aware answer that combines insights from both agents—no juggling multiple interfaces required.

When specialized agents work together behind the scenes, customers can get a unified experience and employees can get time back.

That’s exactly the kind of impact Coca‑Cola Beverages Africa is realizing today by using Copilot Studio agents and Microsoft Dynamics 365 to autonomously run planning cycles and automate workflows end to end, saving planners 1 to 1.5 hours every day.

These features will be fully available to all eligible customers as of April 2026. Three capabilities, one outcome: agents that can operate more like a system and less like a collection of disconnected point solutions.

Build prompts faster while maintaining control

As agent experiences grow more sophisticated, the quality of the prompt an agent maker uses matters more. A great prompt yields more powerful results from agents than a good prompt, and fine-tuning prompts is key to unlocking them.

But in practice, prompt iteration has historically felt disjointed and slow. Makers previously balanced their flow of work with jumping into a separate editor, making a small change, testing it, and then repeating the process again. That friction can add up quickly, especially when teams are tuning prompts for specialized business scenarios.

The new immersive Prompt Builder, now generally available, helps reduce that friction by bringing prompt editing directly into each agent’s Tools tab. You can update instructions, switch models, add inputs or knowledge, and test changes—all in one place. Instead of breaking context every time you want to refine an agent’s behavior, you can iterate while staying grounded in the agent you’re building.

This matters most in real-world scenarios where prompt behavior is tied to domain knowledge and policy nuance. For example, a team building an agent to support clinical documentation might need to refine instructions, swap in a better knowledge source, and test outputs against terminology that is common in healthcare but more likely to trigger default safeguards. Doing that from one workspace can make iteration faster and help lower the effort required to get a production-ready result.

More options for prompts: Content moderation and model choice

Speaking of triggering default safeguards, Copilot Studio has also added content moderation settings for prompts, now generally available in supported regions. This gives makers more control over harmful content sensitivity on managed models, including turning down that sensitivity to help unblock legitimate scenarios in industries like healthcare, insurance, and law enforcement, where default settings may be overly restrictive for the content being processed.

For even more control over prompts, the Prompt Tool now supports Anthropic Claude Opus 4.6 and Claude Sonnet 4.5 in paid experimental preview in the United States. That gives makers more choice in matching the right model to the right prompt, rather than forcing every scenario into the same tradeoff profile. This feature is great for teams that want more flexibility in how they balance performance, reasoning depth, and cost.

All together, these improvements help teams move faster on prompt iteration while maintaining the control and flexibility required in production scenarios.

What else is new and improved in Copilot Studio

We have also recently released several additional updates across automation, meetings, retrieval quality, and model support.

• ServiceNow and Azure DevOps connector quality improvements are now generally available. These help agents better understand operational questions, retrieve the right ticket or work item data, and return more complete, actionable answers automatically.
• Evaluation automation APIs are now generally available through Microsoft Power Platform APIs and connectors. These APIs help make it easier to run evaluations programmatically and integrate quality checks into continuous integration and continuous delivery (CI/CD) workflows.
• Agents for Microsoft Teams meetings can now access real-time meeting transcripts and group chat. This supports scenarios like answering questions during the meeting, surfacing relevant information, or helping track decisions and follow-ups as they happen.
• Model context protocol (MCP) apps and Apps SDK support have expanded how agents connect to your external work apps, helping to make it easier to integrate business systems and enable agents to take action across your broader ecosystem—not just respond with information.
• Additional model support, including Grok 4.1 Fast, GPT-5.3 Thinking, and GPT-5.4 Instant in paid experimental preview, gives makers more options as they tune experiences for speed, cost, and capability.

Overall, these updates reflect a continuing broader shift in Copilot Studio: moving from building individual AI experiences to building connected, governed systems that can fit more naturally into how work already happens. As you scale up your organization’s use of multi-agent ecosystems, these will help your teams reach further across channels and knowledge sources to more accurately fulfill your business needs.

Stay up to date on all things Copilot Studio

More is coming in April 2026 across voice channels, workflows, and the building experience. Check out all the updates as we ship them, as well as new features releasing in the next few months here: What’s new in Microsoft Copilot Studio.

To learn more about Microsoft Copilot Studio and how it can transform productivity within your organization, explore Copilot Studio features and pricing or sign up for our free trial today.

Build powerful agents

Create, customize, deploy, and manage agents with Copilot Studio—and explore the features, use cases, and resources that help you get there.

Try Copilot Studio today

The post New and improved: Multi-agent orchestration, connected experiences, and faster prompt iteration appeared first on Microsoft Copilot Blog.