This article is contributed. See the original author and article here.
What’s one of the most persistent challenges in customer service? The last mile.
A resolution might be proposed, but what happens next often falls into a gray zone. Agents are waiting for a response, customers are going silent, SLAs are creeping past their due dates. It’s inefficient, inconsistent, and frequently unnoticed until metrics start to dip.
With the latest release, Customer Management Agent (CMA) addresses this decisively. CMA now handles follow-up and case closure in a fully autonomous way, delivering consistency, compliance, and operational clarity at scale.
From resolution to closure, without the gaps
Once a resolution is proposed, either manually or autonomously, CMA initiates a structured follow-up process:
Confirmation outreach: CMA automatically checks in with the customer to validate if the issue has been resolved.
SLA-aware reminders: Follow-ups are timed according to defined SLA policies and escalation thresholds.
Closure logic: If the customer confirms resolution, or remains unresponsive beyond the configured threshold, the case is closed automatically, with full traceability.
This not only reduces the manual workload, it ensures timely and consistent case closure.
Sentiment-savvy and context-aware
Case Management Agent doesn’t just check for a response, it interprets it.
For instance:
A “Thanks, this worked!” leads to confident closure.
A “Still not working” escalates the case and re-engages resolution workflows.
Ambiguous replies or no response? CMA applies retry logic and closure rules to make informed, policy-aligned decisions.
The agent operates with human-like judgment—at scale, with precision.
Controlled autonomy, by design
Autonomy doesn’t mean giving up control. With CMA, administrators have granular configuration options to tailor automation to their organization’s structure, policies, and customer expectations.
Admins can configure:
Automation level: Fully autonomous (no human intervention), semi-autonomous (human oversight included)
Field mappings and related entities for AI-based updates
Follow-up and closure email templates
Number, timing, and frequency of follow-ups
Business rules for closure, including SLA thresholds and exception handling
This ensures autonomy serves the business, not the other way around.
Why this changes the game for your team
Autonomous follow-up and closure goes beyond efficiency:
Reduces time and effort spent managing post-resolution tasks
Minimizes operational overhead by eliminating unnecessary manual steps
The road ahead
As organizations scale and customer expectations continue to rise, intelligent closure will become standard, not optional. CMA delivers this capability in a way that’s flexible, reliable, and easy to govern.
Because in modern customer service, a resolved case isn’t truly complete until it’s closed, intentionally and intelligently.
This article is contributed. See the original author and article here.
Frontier Firms put Copilot, agents, and agentic business applications at the core of their operating model to enrich employee experiences, reinvent customer engagement, reshape business processes, and bend the curve on innovation. Today, we’re announcing several new agentic capabilities to help customers move to the Frontier—read on to learn more.
Earlier in 2025, we introduced our vision for how AI agents will transform critical sales processes like building pipeline and qualifying leads. Today marks the next milestone in that journey with the Microsoft Sales Development Agent, available through the Frontier Program in December 2025. Many sales organizations are under pressure to deliver more revenue with limited resources, and the Sales Development Agent helps sales teams scale their impact. This allows sellers to focus on nurturing customer relationships and closing deals.
Features include:
Revenue and pipeline growth: The agent continuously researches prospects, crafts personalized outreach, and automatically follows up to ensure no lead is left behind.
Scalability: Fully independent, yet collaborative, the agent acts as a teammate, with the ability to hand off leads to human sellers when needed.
Security and governance: Built on Microsoft’s trusted security and compliance foundation and when enabled with Agent 365, the agent adheres to robust policies and access controls to ensure user data and workflows are protected.
Sales Development Agent connects with leading CRM systems like Salesforce and Microsoft Dynamics 365, and the Microsoft 365 apps your teams already use like Microsoft Outlook and Microsoft Teams.
The Microsoft sales team is among the first to use Sales Development Agent to reinvent the sales engagement process. With the use of Sales Development Agent, there was a 15.1% increase in the lead-to-opportunity conversation rate. 1
Sales leaders want to help sellers act on more leads, reach more customers, grow faster, and improve revenue per seller. Microsoft Sales Development Agent can make that possible by creating an infinitely scalable sales organization, so no lead is left behind. Accenture plans to pilot Sales Development Agent across our global inside sales-as-a-service business—which helps clients sell to customers around the world—to boost their reach and revenue while maintaining cost to serve. We’ll use what we learn to help clients leverage Sales Development Agent, scale their teams, and unlock new growth.
—Chris Hergesell, Sales Reinvention Lead, Accenture Song
In October 2025, we shared our vision for agentic business applications—built on agents, Copilot, and unified data. These components are what define Dynamics 365 as a system of action.
Today, we’re taking that vision further with updates to Model Context Protocol (MCP) servers across Dynamics 365 and Microsoft Power Platform, strengthening the foundation for agentic capabilities across your entire business. MCP servers are configurable bridges between the business data within your line-of-business (LOB) apps, and the agents you build using tools like Microsoft Copilot Studio. It serves as a universal intermediary, unlocking a unified platform agnostic access to app data, modernizing how AI agents are interoperable with your apps.
For customers of Dynamics 365 Sales and Customer Service, we’ve used MCP to simplify integration between agents in Dynamics 365 and the platforms used by sellers and service reps to execute complementary workflows, like lead research, engagement, and qualification, as well as case management and case resolution, available in public preview on November 21, 2025.
For customers of Dynamics 365 ERP, we are announcing the public preview of the MCP server that unlocks hundreds of thousands of ERP functions for real-time use. We are also introducing a new analytics MCP server in public preview starting in December 2025. These two servers provide a secure, standardized foundation to connect ERP data with AI-powered analytics, helping customers make faster, more accurate decisions and innovate without sacrificing governance.
We are also announcing the Power Apps MCP server in public preview that enables agents to seamlessly trigger app capabilities such as approvals, form submissions, and data retrieval. This makes every Power App a composable, reusable building block in your organization’s AI ecosystem empowering both citizen and professional developers to expose app functionality to agents with confidence and control.
Lastly, the Dataverse MCP server, now generally available, allows people to benefit from natural language interactions, receiving real-time answers grounded in Dataverse data, while makers and admins gain powerful, built-in tools for data operations, search, and prompt execution.
We see tremendous excitement from customers and partners for agentic Dynamics 365 applications. Take Ramp, a financial operations platform designed to save companies time and money. Ramp built an agentic solution, currently in preview, using Microsoft Foundry that integrates with Dynamics 365 Business Central and Teams to streamline employee expense management.
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1 Internal Microsoft sales team data based on time period January 1 to November 7, 2025. Total customers outreach by the agent: 61,734. Lead-to-opportunity ratio (sales qualification): 15.1%.
This article is contributed. See the original author and article here.
In today’s fast-paced digital landscape, customer expectations are higher than ever. They demand swift, accurate, and personalized support—without the friction of long wait times or repetitive interactions. Autonomous case resolution will redefine how support cases are managed and resolved.
What is autonomous case resolution?
Autonomous case resolution is a specialized sub agent within the broader Case Management Agent (CMA) ecosystem. It uses the identified intent to autonomously generate email responses after a case has been created, ensuring customer issues are resolved with minimal human intervention efficiently, intelligently, and empathetically.
Real-world impact
Imagine a customer emailing a business about a defective product. The AI agent reads the email, identifies the issue, uses a custom agent to check the warranty status, and sends a replacement confirmation—all without human involvement. If the customer’s message is ambiguous, the agent requests clarification. If there’s no response, it escalates appropriately. This level of autonomy not only accelerates resolution times but also frees customer service representatives to focus on more complex, high-touch interactions.
Key features and capabilities
With Case Management Agent now generally available, customers can use several groundbreaking features of autonomous case resolution:
Intent-based resolution: The agent automatically determines customer intent and, based on that, drafts and sends an email, ensuring faster resolution.
Autonomous email drafting: The agent crafts professional, empathetic responses using predefined templates (if configured) tailored to various scenarios. Autonomous case resolution can also fall back to default email template replies, or inline email assist in case an email template cannot be identified.
Custom agent integration: The agent can call upon other specialized agents to handle domain-specific tasks, ensuring seamless collaboration.
Smart escalation and handoff: If a customer’s intent remains unidentified, the case is escalated to customer service representatives. When an autonomous resolution is sent but the customer remains unresponsive for a defined period, the case follow-up and closure sub agent istriggered to ensure timely closure.
Multi intent handling: The autonomous case resolution feature handles multiple customer concerns in a single case. By resolving issues sequentially within one interaction, it delivers a unified experience for customers and reduces duplication for support teams.
The road ahead
Autonomous case resolution is more than just a tool, it’s a glimpse into the future of customer support. As it continues to evolve, it paves the way for a fully autonomous contact center experience, where AI agents handle the bulk of interactions, ensuring faster resolutions and higher customer satisfaction.
This article is contributed. See the original author and article here.
Customers expect quick and smooth help when they reach out to customer support—whether it’s about a delayed order, a product question, or a service issue. Good case management means keeping track of all these requests and associated customer conversations to make sure nothing falls through the cracks.
Managing these cases is not always easy. Fortunately, the case create and case update capabilities of the Case Management Agent (CMA) make life easier for support teams and hence, customers.
From manual to automated
A case is like a digital record that holds all the details about the support request. Traditionally, whenever a customer contacts customer service—by chat, email, or voice—a service rep creates a case and manually tracks the issue from start to finish. Now, case create and case update capabilities make this process smarter and more automated than ever.
Key features and capabilities
We released the first version of CMA in public preview in April 2025, and now it’s generally available. We’ve taken customer feedback into account and added capabilities to make creating and updating cases more holistic than ever:
Automatically create a case from chat when the customer service representative accepts the chat request and automatically update it at the end of the conversation. These capabilities are now supported for voice calls and social channels as well.
When the conversation ends, the conversation summary is posted as a note on the case timeline.
For any incoming customer email, case will be created through automatic record creation (ARC). The case will be kept updated with details from all incoming customer emails.
The ability to configure rules based on which case or related entity fields will be predicted. This means you can configure a rule that updates a certain set of fields based on the product in discussion.
Lookup fields are now supported for predictions. You can add field descriptions for capturing your business context which gets leveraged by AI for prediction. For example, for case category prediction, you can describe what each case category means in your business.
We have made changes to the administrator settings layout and in the service rep experience when AI updates are made to the case they’re viewing. This will ensure a more intuitive experience.
You can leverage multiple queue support in automatic record creation (ARC) for creating cases from emails.
Example scenario
Let’s say a customer sends an email to customer support about their device not working properly. As soon as this email is received, Case Management Agent creates a case with the relevant details from the customer’s email. The AI agent answers the email to request further details to solve the issue. The customer sends an email answering AI agent’s questions.
In a pre-CMA world, the customer service rep would have to input these details in the case manually. Not anymore! CMA updates the configured case or related entity fields automatically using this new email from the customer. Everything is kept in one place, so the next agent who helps the customer has the full story—no confusion, no delays.
This article is contributed. See the original author and article here.
Over the last few months, our scheduling team has focused on strengthening the core product by addressing the real-world needs of dispatchers, admins, frontline workers, and managers. At Microsoft, our commitment to continuously improving the Field Service experience is rooted in a simple principle: listen to our users, learn from their feedback, and deliver enhancements that make their work easier and more efficient. Today, we’re excited to announce a suite of user experience improvements that are already live in the product, each inspired by your feedback and design to provide immediate value.
What’s New for Scheduling Users?
Share a Schedule Board Tab Directly from the App
Collaboration is at the heart of effective scheduling. Previously, sharing a schedule board tab with specific other users required a lengthy, complicated process. With this release, you can now easily share any schedule board tab with your colleagues directly from the schedule board settings window. Whether you’re handing off coverage for a vacation or collaborating across teams, sharing your setup is just a few clicks away with no more tedious URL construction or lost productivity.
Short Booking Truncation: Clarity at a Glance
We’ve heard from many of you that when schedules are tight and dense, short bookings often appeared cluttered, with overlapping icons and hastily truncated text. Our redesign cleans up the appearance of these short bookings, dynamically adjusting how much text is displayed and which icons are shown based on the available screen space. We’re making it easier for users to work more efficiently by making the information easy to interpret
Satellite Map View
For those who need a geographic perspective, we’ve brought back a satellite map view. This visual enhancement helps you better understand resource and work order locations and plan routes with greater context.
Address Input for Organizational Unit Locations
Setting up new organizational units or managing the ones you already have should be quick and error-free. Instead of manually entering latitude and longitude for their locations, you can now input a text address, just like you do elsewhere in the product. We’ll handle the geocoding for you, reducing errors and saving valuable time.
Consistent Naming for Characteristics and Rating Models
We know that inconsistent terminology can be a source of confusion. That’s why we’ve standardized names across the product. “Characteristics” now consistently replace “skills” and “rating models” are used over “proficiency models.” This simple change makes it easier to find the features you need and ensures everyone is speaking the same language.
Visual Improvements Across the Schedule Board
Beyond these new features, you’ll notice a range of visual refinements throughout the schedule board. From refreshed icons to cleaner layouts, these details will make your daily scheduling tasks smoother and more enjoyable.
Keep Giving Us Feedback
Each of these enhancements began with your insights, whether surfaced through direct engagements, surveys, support channels, or the Ideas Portal. We’re grateful for your ongoing partnership and feedback. Please keep telling us what you need and sharing your experiences and ideas. They’re the foundation of our ongoing journey to make Dynamics 365 Field Service the best it can be.
This article is contributed. See the original author and article here.
In our recent blog, we introduced how the Quality Evaluation Agent elevates support excellence by bringing automation, consistency, and intelligence to quality assessments. Now, let’s dive deeper into the evaluation framework at the heart of QEA – the blueprint that defines how QEA evaluates support interactions, what standards it upholds, and how it transforms raw evaluations into actionable insights.
Why use an evaluation framework?
Quality management is more than just scoring support interactions. It’s about defining what “good” looks like for your business and enforcing those standards consistently. The evaluation framework in Dynamics 365 Customer Service and Dynamics 365 Contact Center empowers supervisors to do exactly that – at scale and with precision. It specifies how evaluations happen, the evaluation criteria, and how insights flow back to your team. By establishing this framework, you can set clear expectations for service quality and then let QEA’s AI automate the heavy lifting of evaluating each case or conversation against those expectations.
Core components of the QEA evaluation framework
The framework has three core building blocks that work together to turn raw support interaction data into meaningful quality assessments.
Evaluation criteria
These are structured forms that represent your quality standards. Each criterion can include specific questions (or checkpoints), defined answer choices, and a scoring logic (equal or weighted) for how each answer contributes to an overall score. For example, you might have criteria around issue resolution, accuracy, professional communication, and adherence to policy. QEA comes with out-of-the-box criteria, but you can fully customize criteria to fit your organization’s needs, whether that’s emphasizing compliance for a regulated industry or empathy and tone for a customer-centric culture. You can include detailed instructions in each criterion to guide QEA’s understanding of what to look for.
Evaluation plans
These define when and how evaluations are executed. An evaluation plan lets you decide the scope and frequency for QEA’s evaluations. For instance, you can set QEA to automatically evaluate every support case based on conditions occurring (like a case breaching its SLA, a customer giving a low CSAT, or a conversation sentiment dropping below a threshold). You can also schedule these plans to run on a recurring frequency basis, on occurrence of an event or on-demand that supervisors can run for specific high-priority incidents. This flexibility ensures that the evaluation process aligns with business priorities and workflows, without requiring constant manual oversight.
Evaluations
This is the execution layer where QEA applies your criteria to specific support interactions. When an evaluation runs (as defined by a plan or on-demand), QEA takes a given record (case or conversation) and autonomously analyzes it against the evaluation criteria. It then produces a detailed evaluation output that includes: a quality score (often broken down by section), the predicted answers for each question (with an explanation of why it judged it that way), and actionable insights or coaching recommendations for improvement.
For example, QEA might evaluate a closed case and output a scorecard saying compliance was 100% (all policy steps followed), communication clarity was 80% (noting jargon used in one response), and empathy was 70% (noting that the agent missed an opportunity to acknowledge the customer’s frustration) – and then suggest a coaching tip to the supervisor on empathy. Importantly, the framework allows supervisors to review and approve evaluations before they’re finalized. You remain in control. You can adjust scores or override any AI evaluation, ensuring transparency and trust in the system’s outputs.
Supervisors set up criteria and plans, while QEA carries out evaluations and directs results to dashboards and reports for easy review. This creates an ongoing, automated quality audit that aligns with your defined standards.
With structured standards and AI-driven automation, QEA ensures trust, compliance, and excellence in every customer interaction. Every issue—handled by a new hire, experienced agent, or AI bot—is measured against the same standards, enabling quick identification of deviations and best practices.
Case evaluations in action
Let’s make this concrete with how QEA’s framework applies to cases in Dynamics 365 Customer Service. In a traditional setup, a supervisor might manually review a small sample of closed cases each week to check for quality. This approach leaves many cases unchecked and often catches problems long after the customer interaction is over. QEA changes the game by automatically evaluating every case against your predefined standards during any stage of the case lifecycle.
Here’s how it works for cases: Suppose you have an evaluation plan that runs and checks for all closed cases. An agent closes a support case after resolving the customer’s issue. Immediately, QEA kicks in and uses your set criteria to evaluate that case. It looks at the case timeline (all customer communications, agent responses, emails, case notes, etc.) and answers the evaluation questions you’ve defined.
Evaluation scorecards
Within seconds, QEA produces a scorecard for the case. Key benefits of this approach to case evaluation:
Automated quality checks: Every closed case is assessed without manual intervention. No more worrying that a critical case might go unreviewed. QEA ensures 100% coverage, so even edge-case issues or outstanding agent performances get flagged.
Customizable criteria: You define the evaluation parameters to match your business goals. If customer satisfaction and first-contact resolution are your top priorities, your criteria can reflect that. If compliance and process are paramount (for example, finance or healthcare), you can emphasize those. QEA adapts to what matters most to you.
Actionable insights: Instead of just a score, you get clear feedback on each case. This makes it easy to identify coaching opportunities. For instance, if many cases are showing “missing follow-up confirmation,” you can address that pattern with the whole team or adjust training materials.
Scalable oversight: You can move beyond sampling a few cases and truly evaluate all cases for consistent quality. This scalability is huge – it means your quality program can grow with your volume without additional resources. It also means your quality metrics (like average quality score, or percent of cases meeting all criteria) are based on full data, not extrapolation.
Using QEA for case evaluations ensures every support issue receives thorough, consistent review. This approach helps organizations quickly identify policy breaches, skill gaps, or exceptional service, turning insights into targeted improvements. Ultimately, QEA transforms quality assurance into a continuous process, providing supervisors with a reliable tool for oversight and coaching.
Evaluating conversations
The same evaluation framework that powers QEA’s case reviews also extends to customer conversations – whether live chat sessions or voice call transcripts. In contact centers, conversations are as critical as cases, often more so in terms of customer experience. QEA’s framework is entity-agnostic, meaning it can evaluate any type of interaction.
The Quality Evaluation Agent’s evaluation framework embodies a modern approach to customer service management. Quality isn’t an afterthought but is built into the process at every step. With QEA handling the heavy lifting of evaluations, teams can truly elevate their support excellence by acting on insights and continuously refining the customer experience.
Ready to deliver service excellence with consistency and trust? Explore how to activate the QEA evaluation framework in Dynamics 365 Customer Service and Dynamics 365 Contact Center. Now you can turn every support interaction into an opportunity for improvement.
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