Workforce engagement management in Dynamics 365 helps organizations plan and manage a combined human and AI workforce, operate in real time, and continuously improve service quality.

People and AI working together optimize customer service

Customer service organizations are no longer managing people alone — they’re orchestrating service reps and AI agents working side by side. As AI takes on more work, leaders need a new way to plan, monitor, and improve performance across both human and digital labor.

Today, Microsoft is announcing general availability of workforce engagement management (WEM) in Dynamics 365 Customer Service and Contact Center designed specifically for this shift. It brings forecasting, scheduling, real-time operations, and quality management for both human and AI workforces into the service platform where the work happens.

This fundamentally resets how service operations are planned and managed.

Service leaders are under pressure to deliver exceptional customer experiences, respond to shifting demands, and raise quality standards. Yet many organizations still manage forecasting, scheduling, adherence, quality reviews, and coaching across disconnected tools and manual processes with legacy solutions that struggle to keep pace with modern service operations.

With workforce engagement management in Dynamics 365, organizations can run operations as a connected system. Built on the same data model as customer interactions and cases, workforce planning is grounded in actual service demand—not just historical volume—enabling more accurate forecasts, better staffing decisions, and more consistent service delivery. The result is a more precise, responsive operating model that helps organizations meet service levels, maintain quality, and scale AI, without adding complexity.

As an early adopter, we’ve worked closely with Microsoft to evaluate Workforce engagement management in Dynamics 365 against the rigor required in financial services. The platform’s ability to unify human and AI workforce planning, real-time operations, and quality management in one system is a clear differentiator. This supports our relationship-focused, customer and client-centric approach, while reinforcing our risk-disciplined operating model.”

— Jason Pope, EVP and Chief Technology Officer, Flagstar Bank

Plan with confidence

Workforce engagement management in Dynamics 365 starts with planning but in a fundamentally different way. Forecasts are built on real customer signals, including cases, conversations, and channel activity, rather than relying on disconnected inputs.

Capacity planning translates demand into staffing needs, allowing supervisors to model service representative capacity against service-level goals, handle times, concurrency, and operational assumptions.

From there, scheduling aligns the right customer service reps to the right work, shifts, and activities. Because planning and execution share the same foundation, organizations can better match staffing to demand, reduce variability in service levels, and create more predictable workloads for employees.

Evolve the human and AI workforce plan with AI Agent Estimator

As AI agents take on a growing share of service interactions, workforce planning must evolve to reflect a blended workforce.

AI Agent Estimator provides the ability to forecast AI agent capacity and projected usage alongside human staffing. Planners can model how expected demand translates into both human effort and AI usage before those decisions impact operations or budgets.

This provides a more complete workforce plan, giving finance teams visibility into projected AI usage, operations leaders the ability to balance human and AI capacity, and IT teams a way to validate assumptions ahead of scale.

Operate in real time: adherence and shift-based routing

Planning alone is not enough in an environment where conditions shift throughout the day.

Real-time adherence provides visibility into how work is tracking against schedules, helping supervisors identify and respond to changes in agent activity, demand spikes, or service-level risk.

Shift-based routing connects workforce planning with service execution by aligning routing decisions to actual availability. Work is directed to customer service reps who are scheduled and ready, improving efficiency and reducing delays.

Together, these capabilities allow organizations to respond to demand as it happens, rather than reacting after service levels have already been impacted.

Move from manual spot checks to continuous quality improvement

Workforce engagement is not only about having enough people available. It is also helping with standards for empathy, compliance, resolution quality, and process execution.

Quality Evaluation Agent helps supervisors deliver more consistent, scalable quality oversight. Teams can define evaluation criteria, configure evaluation plans, and use AI-led assessment to evaluate customer interactions across cases and conversations, surfacing strengths, gaps, and coaching opportunities at scale. Because quality evaluation can use case context and operational data from Dataverse, it can assess service outcomes in the context of the customer record, not only the transcript.

Screen Recording adds another important signal: what happened on the screen while work was performed. For complex service interactions, quality depends not just on what was said, but on whether the rep followed the right steps across systems. Conversations, transcripts, and case notes explain what was said and documented, while screen context shows how the rep navigated systems, used knowledge, and completed the workflow.

Governance helps organizations turn policy expectations into consistent, explainable checks. Administrators can define policies in plain language and use them to evaluate whether customer communication is compliant, brand-safe, regionally appropriate, and aligned with company standards.

Coaching skills can convert quality signals into improvement plans by combining screen recording intelligence, governance outcomes, configured playbooks, evaluation rubrics, and gamification. Screen recording provides evidence of what happened, governance provides the policy signal, and playbooks define what should have happened.

The result is a closed-loop Quality Management model: capture screen and conversation context, evaluate with Quality Evaluation Agent and governance policies, coach with playbooks and improvement plans, motivate with gamification, and feed learning back into operations and workforce planning.

Built on the Microsoft cloud and Dynamics 365 platform

Workforce engagement management in Dynamics 365 works out of the box, with the flexibility to extend through the broader Microsoft platform as needs grow, from Dataverse and Teams to Power Platform, Copilot Studio, Azure AI, and Microsoft security and compliance foundations.

That breadth matters because WEM is not a standalone system that organizations have to wire together themselves. It is part of the service platform where customer interactions, workforce plans, quality signals, AI-assisted workflows, and collaboration come together in one operating model.

Bringing these signals together creates a stronger operating model for supervisors, customer service reps, and service leaders.

Adopt workforce engagement management on your terms

Organizations are at different stages in their workforce management journey. Some are ready to move quickly to native WEM capabilities in Dynamics 365. Others have existing workforce management investments and need a practical path forward.

Adapters for solutions such as Verint, Calabrio, NICE, and Alvaria help customers connect those existing systems with Dynamics 365 service operations, reduce integration friction, and transition to more native workforce engagement management capabilities over time.

Customers should not have to choose between modernization and continuity. Workforce engagement management in Dynamics 365 is designed to support both.

The next phase: agentic workforce engagement management

Over the coming few months, our workforce engagement management MCP tooling will make core workforce actions available through agent-ready tools across Microsoft 365 surfaces such as Service Agent, Teams, Copilot, and mobile. This will allow supervisors and service reps to complete high-value WEM tasks—such as viewing schedules, checking leave balances, submitting time-off requests, managing shift swaps, clocking in and out, and acting on approvals—all through natural language prompts, without needing to navigate the full Dynamics365 application.

By separating the WEM business capability from the user experience surface, WEM MCP tools will create a reusable foundation for key WEM features for mobile access, Copilot experiences, Teams workflows, and future agentic scenarios.

A better way to run service operations

Workforce engagement management in Dynamics 365 Customer Service and Contact Center brings planning, real-time operations, and quality management into the flow of service. The result is a more connected operating model for managing customer service reps and AI agents, with the flexibility to modernize over time.

Generally available today

Workforce engagement management in Dynamics 365 is generally available on June 30, 2026. It is included with Dynamics 365 Customer Service Enterprise and Premium SKUs, and available with Dynamics 365 Contact Center Voice + Digital SKU.

Next step: Learn more about workforce engagement management capabilities in Dynamics 365 on Microsoft Learn.

The post Optimize workforce operations across people and AI agents with Dynamics 365 appeared first on Microsoft Dynamics 365 Blog.

Customer experience leadership in the age of AI is undergoing a massive transition. Leaders are expected to act in the moment, but the systems, incentives, and data around them are often not designed to support it. The Microsoft 2026 Work Trend Index is clear: the constraint on transformation is not people, but the gap between what employees can do and what organizations are built to support.

That shift is creating new pressure in customer experience. Leadership roles like supervisors face more critical choices than ever. When should AI handle an interaction versus a service rep? How should teams respond to shifting demand across channels? Where does a coaching moment belong in the flow of a live conversation? In disjointed environments, the data needed to answer these questions arrives late or incomplete, producing fragmentation tax. What was once a role defined by queue management and reporting is now defined by real-time judgment, prioritization, and accountability for the customer experience.

Microsoft Dynamics 365 is built around this new reality and the evolving role of customer experience leadership. 

Today, we are making three announcements that strengthen a leader’s ability to manage modern customer experience operations.

1. First, as AI expands across both contact center and customer service, leaders need a unified system to manage the workforce operating within it. That is why Dynamics 365 now includes a comprehensive set of workforce engagement management (WEM) capabilities—giving leaders a single system to plan, staff, monitor, and improve performance across both AI and service reps. WEM is no longer a separate layer. It is embedded directly into the flow of work, grounded in the same data that powers every customer interaction.
2. Second, Dynamics 365 Contact Center continues to expand AI agents announced in April by embedding new coaching skills into existing workflows that help supervisors provide real-time guidance, analytics, and operational intelligence. These are not standalone tools that add complexity. They are designed to support supervisors in managing a blended workforce, extending their ability to oversee performance, guide outcomes, and scale operations. 
3. Finally, Dynamics 365 Contact Center is introducing new real-time wallboards to help supervisors visualize the performance of the business.

Together, these innovations can elevate customer experience leadership in the era of AI.

Optimizing the new blended workforce with Workforce Engagement Management

Customer service and contact center organizations are no longer managing people alone—they’re orchestrating service reps and AI agents working side by side. As AI takes on more work, leaders need a new way to plan and manage both service reps and AI agents.

With workforce engagement management, Dynamics 365 now delivers a complete customer experience platform that brings together customer service, contact center, and workforce planning in one connected experience. Workforce engagement management is no longer a separate system sitting beside the customer experience. Instead, forecasting, scheduling, adherence, intraday shift swapping, bidding, and time recording are embedded directly into the flow of work, grounded in the same customer and case data that powers every interaction.

For customer experience leaders, this creates a different operating model. Real customer demand, including conversations, email, cases, and channel activity, becomes the direct input to workforce planning. Forecasts are built on actual service interactions, which is only possible when workforce management shares the same data model as the interactions it supports. As a result, organizations can create more balanced, manageable workloads for employees.

By embedding workforce engagement management directly into customer service and contact center, Dynamics 365 creates a closed loop across planning, execution, and improvement. Supervisors plan using real demand signals and operate with visibility into live service conditions, while employees benefit from clearer expectations, more responsive scheduling, and real-time coaching. As conditions shift, whether due to changes in channel mix, spikes in demand, or increased automation, the same operational context feeds back into planning so both customer and employee experiences continuously improve. 

In addition to the generally available purpose-built autonomous agents (Customer Intent, Knowledge Management, Case Management, Quality Evaluation), Dynamics 365 Customer Service is expanding on the same principle. Recent additions—Microsoft 365 Copilot embedded directly in the product, the Dynamics 365 Customer Service plugin for Copilot Cowork, and Service Agent in Microsoft 365 Copilot ensure service professionals have unified intelligence and the ability to act wherever they work. 

Turning every customer interaction into a high-quality moment

In many environments, supervisors are still working across disconnected systems for routing, quality, and AI. Each solution provides a partial view, requiring supervisors to stitch together insights manually. This fragmentation introduces delays, increases cognitive load, and limits the ability to act in real time. Dynamics 365 removes this fragmentation by bringing multiple signals into a single platform. Supervisors can operate from one system with a consistent view of demand, performance, and quality.

Quality Assurance Agent, aligned with the supervisor role in the contact center, now introduces real-time coaching (generally available) by shifting it into the flow of the interaction itself. Rather than relying on post-call reviews, supervisors operate in an environment of continuous, real-time coaching where every conversation, across voice, digital channels, human agents, and AI agents, is monitored, assessed, and improved in the moment.

At the core of this capability is a real-time evaluation engine powered by the Quality Assurance Agent, which continuously scores interactions against configurable quality criteria such as communication, empathy, compliance, and effectiveness. Supervisors gain immediate visibility into these scores at both the aggregate and individual conversation level, allowing them to identify quality gaps as they emerge, not after the interaction is complete. This transforms quality from a retrospective activity into a live operational signal that can directly influence outcomes while the customer is still engaged.

At the same time, AI-powered coaching nudges are delivered directly to customer service reps in context, providing specific, situational guidance such as prompting for clearer next steps, reinforcing empathy, or flagging compliance risks. These nudges are not generic suggestions but are triggered based on real-time signals from the conversation, helping agents stay on track and improve performance moment by moment.

This model introduces a human-in-the-loop approach where supervisors define the rules, thresholds, and playbooks that guide how AI coaching is delivered, while maintaining full visibility and control over how AI is applied. Supervisors are notified in real time when quality dips or compliance risks are detected, enabling immediate intervention and reducing the likelihood of negative customer outcomes. The result is a closed-loop system where detection, guidance, and action happen continuously, ensuring that quality is enforced and improved at scale without adding manual overhead.

In April, Microsoft introduced three coordinated AI agents for Dynamics 365 Contact Center as part of its shift to Agentic CX. In addition to Quality Assurance Agent, Customer Assist Agent handles frontline interactions across voice and digital channels with real-time voice and seamless escalation, while Service Operations Agent focuses on setup, configuration, and ongoing optimization. Together, they extend coverage from engagement through operations within a single connected system.

Turning data into decisions

As the number of operational choices increases, the need for clear, actionable data becomes critical. This reduces uncertainty, improves consistency, and enables supervisors to manage with confidence rather than intuition alone.

Dynamics 365 Contact Center is also introducing new real-time wallboard capabilities to enable organizations to track contact center metrics through a ticker-style experience, giving supervisors immediate insight into service levels, backlog, and performance as conditions change. This allows teams to respond faster, helping maintain consistent customer service levels while reducing the need for manual monitoring and status checks.

Choosing a holistic customer service platform leaders can rely on

As organizations evaluate AI investments, the number of options continues to grow. Many approaches add new tools without addressing underlying fragmentation, increasing the burden on leadership and supervisors.

The advantage comes from choosing a platform that supervisors can rely on. One that unifies data, embeds AI into operations, and reduces complexity rather than increasing it.

Microsoft Dynamics 365 provides that foundation. By bringing customer service, contact center, workforce engagement, and AI together on a single data model, it enables leaders to operate with clarity, consistency, and control.

Workforce engagement management, real-time coaching, and real-time wallboards in Dynamics 365 is generally available. It is included with Dynamics 365 Customer Service Enterprise and Premium SKUs, and available with Dynamics 365 Contact Center Voice + Digital SKU.

Next steps

• Read more about workforce engagement management capabilities in Dynamics 365 here on our Dynamics 365 IT Professional Blog.

The post Customer experience leadership in the age of AI: A new operating model with Dynamics 365 appeared first on Microsoft Dynamics 365 Blog.

Most contact center platforms still treat routing as the defining moment in a conversation. But the customer journey continues to evolve after that first decision. Intent changes. Wait times increase. Workforce availability shifts. Business priorities move. Each of these real-time signals shapes the experience. This creates an opportunity to manage the conversation lifecycle more effectively — not as a one-time routing event, but as a dynamic journey guided by live context from both the customer and the contact center. 

Contact centers are constantly balancing customer need with workforce capacity. ACD has always helped manage that balance, but when conditions change, service levels, satisfaction, and trust change with them. That balance cannot be set once and left alone. It has to be sensed and adjusted in real time. Otherwise, supervisors are forced to step in manually, often after the moment to act has passed. What contact centers need is not more static logic, but a system that can continuously sense, decide, and respond as the conversation unfolds.

Introducing conversation orchestration in Dynamics 365 Contact Center

In April we introduced conversation orchestration, a new tool within Service Operations Agent. It extends traditional routing by enabling the contact center to respond dynamically as conditions change. It allows administrators to define business policies in natural language using a model of events, conditions, and actions.

Conversation orchestration continuously monitors signals across the conversation lifecycle, evaluates them against the configured playbook, and triggers the appropriate response. The result is a more adaptive operating model that helps contact centers manage change in real time and deliver more consistent customer outcomes. We will continue to expand conversation orchestration over time by adding capabilities — each one targeting a specific, high-impact contact center use case. The first two are available today. 

Policies written in natural language. Executed at scale. 

The hardest part of building intelligent contact center behavior has never been the technology. It has been the configuration. Rule trees that take weeks to build, require IT to modify, and break in ways that are invisible until a customer notices. The expertise of your best operations leader, locked inside a configuration file that nobody else can read or change. 

Conversation orchestration replaces that with playbooks — natural-language instructions that define what should happen at each stage of the conversation journey. An admin does not configure a rule. They write an intention: 

“If a premium customer is waiting in the queue and no support reps are available, increase their priority over time.”

“If a premium customer is waiting in the queue unassigned, immediately offer a callback.”

That is the entire instruction. Conversation orchestration handles the rest: reading the conversation context in real time, evaluating the conditions against customer attributes from CRM, executing the action, and doing it with consistency that no manual process can match. 

Guided templates make common scenarios fast to configure. Built-in validation catches conflicts before anything goes live. What used to require a specialist and a change management process can now be authored, validated, and published by an operations admin in minutes. 

This is the difference between a system that routes and a system that orchestrates. 

The first set of capabilities: available now in Public Preview

We are launching conversation orchestration with first set of capabilities in public preview. They are not arbitrary starting points. They address the two most universal failures in contact center queue management — the ones that affect nearly every enterprise contact center, every single day.

Dynamic prioritization 

Priority set at queue entry and never revisited is one of the most quietly damaging problems in contact center operations. A customer waiting ten minutes is competing for the same representative as someone who just arrived. A conversation transferred mid-journey — carrying all the context of what came before it — resets to the destination queue’s default priority as if it had just called in. 

Dynamic prioritization fixes this by keeping priority evaluation alive throughout the conversation. As wait time accumulates, as transfers occur, as customer tier is confirmed from CRM — the priority score adjusts automatically. High-value customers and long-waiting callers move forward without anyone monitoring the queue manually. Conversation orchestration does what the best supervisor would do, but for every conversation simultaneously. 

Overflow based on customer service availability 

When no customer service representatives are available, the standard contact center response is silence. The customer waits. Maybe a representative comes online. Maybe they do not. Overflow rules exist in some systems, but they wait for a fixed timer to expire before doing anything — which means every customer experiences the same minimum wait regardless of whether help is actually coming. 

Overflow based on customer service representative availability acts the moment it is needed. As soon as a conversation enters a queue with no eligible representatives — accounting for skills, capacity, and assignment logic — the overflow playbook fires. And the action it takes is not the same for every customer. Context variables determine the outcome: one segment transfers to a backup team, another receives a callback offer, a third gets a graceful closing message. Every customer gets a response. None of them wait in silence. 

Try It Today 

These two capabilities are the first step in a broader orchestration platform. We will be enabling more scenarios enabling you to automate the contact center behavior.

Conversation orchestration is available now in public preview for voice and live chat channels in Dynamics 365 Contact Center. Access it through Copilot Service admin center under Get started > Contact Center Agents > Service Operations Agent(preview) > conversation orchestration (Preview).

Start with a template, configure your first playbook, and see what it means for a contact center to stay with every conversation — not just route it. 

Learn more 

• Configure conversation orchestration (preview) | Microsoft Learn 
• Dynamic Prioritization | Microsoft Learn 
• Overflow Based on CSR Availability | Microsoft Learn

The post Introducing Conversation Orchestration in Dynamics 365 Contact Center  appeared first on Microsoft Dynamics 365 Blog.

For years, contact centers have relied on traditional IVR scripted workflows to manage customer conversations. While effective for predictable tasks, these solutions become brittle as interactions grow more complex or multi‑step. Every change—whether updating policies, adding new intents, or refining flows—requires manual reconfiguration. This makes IVRs expensive and time‑consuming to maintain at scale. At the same time, many new standalone AI voice solutions swing too far in the other direction. They offer flexibility but struggling to deliver the control, reliability, and consistency enterprises require.

With Customer Assist Agent in Dynamics 365 Contact Center, Microsoft introduces a new model: a GenAI‑driven solution that owns the customer interaction end‑to‑end, evolving traditional IVR into something far more capable. Rather than forcing a choice, it combines structured voice processing with generative reasoning. This enables both precise, controlled workflows and natural, conversational interactions within the same experience.

Managed in Microsoft Copilot Studio and natively integrated into Dynamics 365 Contact Center, Customer Assist Agent unifies AI, workflows, and enterprise data into a single solution.

Evolving IVR

Traditional IVR systems were built for structured intents and predictable outcomes. They rely on deterministic pipelines that decompose conversations into a sequence of predefined steps. They convert speech to text, classifying intent, selecting a dialog path, and then generating a response.

This approach works well for simple, single‑intent scenarios. Because each step follows a predefined flow, the system cannot understand the interaction as a whole. It struggles to adapt in real time when conversations deviate, whether through interruptions, topic changes, or multiple intents expressed at once.

As interactions become more complex, this model breaks down. Dialog trees grow exponentially, maintenance becomes increasingly costly, and even small changes require reauthoring and testing across multiple paths. The experience feels constrained and unnatural. It often fails to resolve customer needs in a single interaction, leading to unnecessary escalation to a human representative.

Customer Assist Agent takes a different approach. Rather than replacing IVR, it absorbs it into a more intelligent solution. Customer Assist Agent listens continuously, reasons in the moment, and responds naturally. It also preserves the enterprise requirements IVR has always delivered: reliability, compliance, predictability, and scale. Customers can speak naturally, interrupt freely, and express multiple intents without resetting the interaction or navigating menus.

Modernizing voice does not mean abandoning enterprise‑grade capabilities. Customer Assist Agent includes support for DTMF input and fallback, silence detection and speech tuning, latency signaling, secure transfers to agents, and multi‑language interactions without pre‑routing. These capabilities are foundational for delivering voice at scale and ensure that GenAI enhances reliability rather than undermining it.

At the same time, conversations are no longer constrained by language. Customer Assist Agent with speech‑to‑speech (direct, real‑time audio interaction with the model) supports multi‑language interactions with dynamic language switching, allowing customers to move naturally between languages within a single conversation.

One Solution Across Self-Service and Assisted Service

Customer interactions do not follow clean boundaries between automation and customer service representative support. Solutions need to adapt as fluidly as customers do. Customer Assist Agent provides continuity across the journey.

The same solution can resolve requests autonomously. It can recognize when a human is required and transfer with full context to Dynamics 365 Contact Center. It continues assisting the representative in real time. Equally important, this approach enables incremental modernization. Organizations can preserve deterministic IVR flows where they already perform well, particularly in compliance‑sensitive or mission‑critical scenarios. The solution introduces generative voice capabilities where they deliver the greatest impact on containment, handle time, and customer satisfaction. Voice becomes a solution that continuously improves instead of one that must be redesigned in a single, monolithic upgrade.

For example, a customer calls and says, “My bill is higher than expected. I traveled last month, upgraded my phone mid‑cycle, and I don’t recognize one of the charges.”

• Rather than forcing that conversation into separate, predefined paths, Customer Assist Agent treats it as a single interaction.
• Multiple intents are identified within the same exchange and managed together. This allows the system to reason across them and determine how to proceed.
• Relevant account and billing data is retrieved dynamically. The conversation progresses naturally by addressing each aspect in context, without requiring the customer to repeat or navigate separate flows.  As the conversation evolves, the system maintains a unified view of the interaction, preserving intent, history and intermediate outcomes.
• If human assistance is required, the interaction is handed off with full context to Dynamics 365 Contact Center. This way, the representative picks up exactly where the conversation left off.
• Throughout the process, the system remains engaged. It supports the representative in real time, with context, suggested actions and next steps. This way, the interaction continues without repetition or rework.

To the customer, it feels like one continuous conversation.

Deterministic and Generative — Used Together

Customer Assist Agent combines deterministic control and generative intelligence, using each where it performs best.

Deterministic logic remains essential in moments where outcomes must be precise, repeatable, and auditable.

• Scenarios such as identity verification, payments and refunds, eligibility checks, regulatory disclosures, and the enforcement of hard business rules demand exact behavior every time.
• In these cases, structured flows provide the necessary guardrails, ensuring accuracy, compliance, and confidence—while allowing generative intelligence to operate around them rather than in place of them.

Generative reasoning is applied when conversations are dynamic, ambiguous, or evolve over time, particularly in scenarios such as:

• Troubleshooting issues where the problem is not clearly defined upfront
• Gathering and correlating multiple pieces of information across turns
• Handling interruptions, corrections, or shifts in topic mid‑conversation
• Managing multi‑intent requests without forcing the caller down rigid paths

For example, a customer might say, “I ordered shoes last week—where are they? Actually, just cancel them.”

Rather than treating these as separate interactions, Customer Assist Agent identifies both intents and determines how to handle them in sequence. It first retrieves the relevant order details with generative reasoning, then executes the cancellation using structured, deterministic logic, and confirms the outcome—all within the same conversation.

This illustrates how generative reasoning and deterministic execution work together: the system interprets the request holistically, decides how to proceed, and applies the appropriate approach at each step. The interaction continues fluidly, without requiring the customer to restart, navigate separate flows, or repeat information.

From Answers to Outcomes

Customer Assist Agent doesn’t just respond, it acts.  Through secure, governed connections to enterprise systems including MCP-based tooling and enterprise workflows it can check status, modify accounts, trigger workflows and record outcomes.  Voice becomes a resolution engine, not just a channel.

Because Customer Assist Agent is integrated into Dynamics 365 Contact Center, these actions are connected directly to customer data, case management, and operational systems — ensuring every interaction is both contextual and actionable.

Accuracy That Improves Over Time

High‑quality voice experiences depend on accuracy, and accuracy is no longer static . With Customer Assist Agent, precision improves continuously as the system learns from real customer interactions, evaluates outcomes, and refines its behavior over time. Each conversation becomes an opportunity to identify gaps, adjust responses, and improve how intents are understood and resolved.

Critically, this optimization is not limited to specialists or data science teams. Because Customer Assist Agent is authored and managed in Microsoft Copilot Studio, business users can directly influence performance, tuning behavior, improving accuracy, and optimizing experiences using governed tooling and real operational feedback. Voice intelligence evolves in production, driven by the people closest to the customer experience rather than cycles of retraining and redevelopment.

To support this, Microsoft introduced Model Assessment Score (MAS), a standardized way to measure and track AI agent performance across real interactions. MAS provides a consistent framework for evaluating quality, identifying areas for improvement, and driving continuous optimization.

In practice, MAS enables teams to run structured evaluations and experiments—for example, comparing the performance of different models on the same set of interactions, or testing alternative prompting strategies to improve response quality.  By measuring outcomes consistently, teams can make informed decisions about what works, iterate quickly, and continuously improve performance in a controlled and observable way.

You can learn more about how MAS works in this blog:
http://approjects.co.za/?big=en-us/dynamics-365/blog/it-professional/2026/02/04/ai-agent-performance-measurement/

A New Model for Customer Interaction

Create a Customer Assist Agent in Dynamics 365 Contact Center with Microsoft CoPilot Studio using your existing business policies, data, and tools, then experiment to understand what’s possible.  By testing real scenarios, trying different approaches, and observing how the system responds, teams can quickly build intuition for where generative reasoning adds value and where deterministic control remains essential.

Once you have that foundation, identify a high-value voice scenario where conversations are common, involve some variability, and benefit from more flexible handling than traditional IVR can provide. These are often interactions that sit between simple automation and full human support—where improving containment or reducing handling time can deliver immediate impact without introducing unnecessary risk.

Next use Microsoft Copilot Studio to refine your agent. Define how generative reasoning and deterministic logic work together, connect the agent to the data and actions required to resolve real customer requests, and establish governance and guardrails appropriate for your business. Copilot Studio provides a single place to design, test, and manage voice agents using enterprise‑ready tooling.

Then, deploy alongside your existing IVR and agent workflows. Customer Assist Agent operates in both fully agentic and hybrid environments. It keeps deterministic flows where precision matters and adds generative capabilities where flexibility improves outcomes. This allows teams to modernize incrementally and confidently.

Finally, measure, learn, and refine in production. Use real interaction data and evaluation signals to identify gaps, tune behavior, and continuously improve accuracy and resolution rates. With Copilot Studio, drive optimization by business teams and operators closest to the customer experience, not long retraining cycles.

Voice is the front door to the contact center. With Customer Assist Agent and Copilot Studio, that door can finally understand intent, adapt in real time, and improve with every conversation.

The post Modernize IVR with AI Voice in Dynamics 365 Contact Center appeared first on Microsoft Dynamics 365 Blog.

AI is becoming part of the operational workforce

Customer service operations are entering a new phase of evolution, where AI is no longer just assisting work but actively performing it. In Dynamics 365 Customer Service and Contact Center, AI agents now drive core service workflows every single day. For example:

• Quality Evaluation Agent autonomously evaluates customer interactions against defined criteria, generating scores, summaries, and actionable insights to improve service quality at scale.
• Case Management Agent automates the case lifecycle by creating, updating, resolving, and closing cases using conversation context, reducing manual effort and improving consistency.
• Customer Intent Agent identifies customer intent from conversations, enabling intelligent self-service, guided interactions, and accurate routing to the right resources.

These agents are no longer peripheral tools; they are executing real workloads and contributing directly to business outcomes. This shift changes how organizations need to think about AI. If these agents are doing meaningful work, they are no longer optional enhancements; they are part of the workforce itself.

The Planning Gap: Demand Forecasting Without AI Cost Visibility

While AI adoption has accelerated, workforce planning practices have not kept pace.

Organizations today are well equipped to forecast demand, predicting case volumes, conversation trends, and channel distribution. However, when it comes to AI, a critical layer is missing. Teams often lack clear visibility into how forecasted demand translates into AI usage and, more importantly, into cost.

The challenge is not forecasting demand, but translating that demand into financial impact. Organizations can estimate how much work is coming, but they struggle to answer a simple question: if this is the expected demand, what will it cost in AI usage?

Without a clear mapping between forecasted workload and AI credit usage, planning becomes reactive. Finance teams discover AI costs only after they have occurred. Service leaders lack the data to allocate AI capacity confidently.  Even small variations in demand can lead to unexpected changes in usage, especially as AI handles a growing share of interactions.

Addressing this challenge requires connecting operational forecasting with financial modeling, enabling organizations to plan with both demand and cost in mind.

Introducing AI Credit Estimation in Dynamics 365

AI Credit Estimation in Dynamics 365 Customer Service and Contact Center brings these domains together.

Built on top of the platform’s intelligent forecasting capabilities, it provides a direct and transparent way to translate forecasted demand into expected AI credit usage. Rather than treating AI cost as something to be reconciled after the fact, AI Credit Estimation makes it a first-class planning input alongside case volumes, staffing ratios, and service level objectives.

This allows organizations to move from abstract assumptions to measurable planning insights.

How it works: A Step-by-Step Walkthrough

Here is how to get from volume demand forecast to credit estimate in three steps:

Step 1: Define and Generate a Forecast Scenario

Start by creating a forecast scenario within the Dynamics 365 Customer Service or Contact Center forecasting experience. Specify the planning horizon and include the channels and queues that are in scope.

The platform’s intelligent forecasting model analyzes historical traffic patterns, including seasonal variation, and trend lines  to generate predicted volumes for each queue and channel over your chosen time period. The result is a clear, data-driven view of expected demand.

Step 2: Select the AI Agents to Estimate

With your forecast in place, open the AI Credit Estimator and select the agent whose credit usage you want to model. All out-of-the-box agents available in Dynamics 365 Customer Service and Contact Center are supported, including:

• Quality Evaluation Agent
• Case Management Agent
• Customer Intent Agent

Step 3: Review Your Credit Estimate

Once agent is selected, the estimation engine maps your forecasted workload to projected AI credit usage. The output is a clear, readable credit estimate tied to the queues included in your forecast scenario.

This gives your team a single planning view that shows both expected demand and the associated AI credit cost required to service that demand. From here, teams can validate assumptions, adjust scenario parameters, and refine estimates before committing to capacity planning.

The screen below shows the estimator within the forecast scenario.

Shift Toward a unified workforce model

The deeper significance of AI Credit Estimation goes beyond a single feature. It represents a shift in how organizations can think about and manage AI in their service operations.

Until now, AI agents have often been treated as a separate category, evaluated for capability but not managed with the same financial and operational rigor as human staffing. AI Credit Estimation changes that. When you can forecast demand, estimate AI cost, and compare both against service objectives, AI agents become truly plannable workforce components.

This matters for several reasons:

• Finance teams can include AI credit projections in budget cycles and operational reviews, rather than discovering AI costs after they land on an invoice.
• Service operations leaders can balance human and AI capacity proactively, adjusting the mix based on cost, quality, and service level goals.
• IT administrators and solution architects can use credit estimates to validate deployment decisions and right-size AI agent usage before scaling.

As AI continues to take on a larger share of customer interactions the ability to plan human and AI agents within a unified workforce model becomes essential for both operational efficiency and financial transparency.

Learn more about AI credit Estimation To learn more about AI credit estimation in Dynamics 365 Customer Service and Contact Center, read the documentation on Microsoft Learn.

The post The next frontier of workforce planning: from forecasting to AI usage and Credit Estimation appeared first on Microsoft Dynamics 365 Blog.

As organizations expand globally and adopt AI‑powered customer engagement, complying with call‑recording regulations while maintaining a seamless customer experience has become increasingly complex. To help address this challenge, we’re excited to announce Consent‑Based Recording for voice interactions in Dynamics 365 Contact Center with Microsoft Copilot Studio.

This new capability enables organizations to explicitly capture caller consent within a Voice Agent and automatically apply that consent decision across the entire interaction including when the call is handed over to a customer service representative.

Why consent‑based recording matters

In many countries and regions, laws require explicit customer consent before a call can be recorded or transcribed. Historically, enforcing these requirements across AI Agents, Customer Service Representative (CSR) handoffs, and recording controls have required custom logic, manual CSR checks, or complex integrations.

Consent‑Based Recording simplifies this by making consent a first‑class, system‑enforced signal ensuring that recording and transcription behavior always aligns with the caller’s choice.

How it works

With Consent‑Based Recording, Copilot Studio makers can configure a Voice Agent to request recording consent early in the conversation. Based on the caller’s response:

• If consent is granted
  • The call is recorded and transcribed.
  • Pause/Resume Recording control is available to CSRs in Contact Center Workspace – when the interaction is transferred to them.
• If consent is not granted
  • The call proceeds without recording or transcription.
  • Pause/Resume Recording control is disabled when the voice interaction is handed over to a CSR, preventing any accidental or unauthorized recording.

The consent decision is automatically preserved and enforced throughout the interaction lifecycle no additional configuration or agent intervention required.

Business value

Built‑in compliance for global operations

Consent‑Based Recording helps organizations meet call‑recording and privacy regulations, especially in countries where explicit consent is legally required. It ensures recording behavior is governed by the caller’s choice across both Voice Agent and human‑assisted interactions.

Reduced operational and agent risk

By automatically enforcing consent in the CSR experience, organizations eliminate reliance on manual checks or agent judgment. This significantly reduces the risk of non‑compliant recordings.

Seamless AI Agent‑to‑CSR experiences

Consent captured in the Voice Agent seamlessly carries over during CSR handoff, delivering a consistent and transparent customer experience without disruption or repetition.

Designed for trust and transparency

Consent‑Based Recording reflects Microsoft’s commitment to privacy‑by‑design principles. Customers are clearly informed, their preferences are respected, and agents are guided by UI‑level safeguards that prevent unintended policy violations.

Together, these capabilities allow organizations to confidently deploy Voice Agent and live agent experiences in Dynamics 365 Contact Center, while maintaining regulatory compliance, customer trust, and operational simplicity at scale and across borders.

Learn More

https://learn.microsoft.com/en-us/microsoft-copilot-studio/voice-consent-based-record?branch=pr-en-us-1774

The post Introducing Consent‑Based Recording for Voice Agents and CSR Interactions in Dynamics 365 Contact Center appeared first on Microsoft Dynamics 365 Blog.

In contact centers, operational excellence doesn’t start with the first customer interaction—it starts much earlier, during setup, configuration, and ongoing system health management. Yet for many organizations, these steps remain complex, time-consuming, and error-prone. 

To solve for these, we are excited to preview Service Operations Agent, a new AI-powered capability in Dynamics 365 Contact Center transforming how administrators configure, validate, and orchestrate conversations at runtime.

Why this matters 

Setting up and maintaining a contact center environment often requires navigating multiple tools, understanding complex dependencies, and manually troubleshooting issues. These challenges can result in: 

• Slow onboarding and delayed time to value 

• Configuration errors that impact routing, channels setup 

• Conversations managed by static rules that cannot adapt — ignoring wait time, customer tier, agent availability, or transfer history — leading to poor outcomes that no one is actively watching 

• Limited visibility into system health and operational readiness 

• Reliance on specialized expertise for basic administrative tasks 

These traditional approaches fragment setup, validation, and diagnostics across multiple surfaces—making it difficult to ensure consistency and operational reliability. 

Service Operations Agent addresses these by bringing these capabilities together into a unified, conversational experience. 

What’s new 

Service Operations Agent introduces an AI-powered administration layer built directly into Dynamics 365 Contact Center, enabling administrators to: 

• Set up contact center channels and manage users conversationally 

• Receive recommendations on next steps from agent 

• Dynamic orchestration of conversations to handle needs of a working contact center during run time through playbooks 

• Validate configurations and detect issues early when connected to Application Insights  

• Monitor operational health and troubleshooting guidance 

Together, these capabilities give administrators a single place to set up the contact center, keep it healthy, and define how every conversation is handled at runtime — from first contact through resolution. 

How it works 

Service Operations Agent is available directly within the Dynamics 365 Contact Center Admin Center, where administrators can interact with it using natural language.  

The agent guides users through tasks such as: 

• Setting up channels, queues, workstreams 

• Managing users and skills  

• Applying playbooks using provided templates for dynamic orchestration of conversations  

• Configuration validation and troubleshooting through Application Insights 

This creates a more intuitive and streamlined administrative workflow—reducing complexity while maintaining control and governance. 

Key capabilities in this preview release 

In this preview release, Service Operations Agent focuses on three core areas: setup, diagnostics and conversation orchestration.

Conversational setup and configuration 

Administrators can use natural language to provision and configure key components such as queues and channels—reducing reliance on manual configuration flows. This approach streamlines onboarding and helps organizations get up and running faster, even without deep technical expertise.  

Intelligent validation and diagnostics

Service Operations Agent continuously evaluates configurations and surfaces potential issues, helping administrators: 

1. Identify misconfigurations early 

2. Understand root causes of setup issues 

3. Receive actionable recommendations for resolution 

Embedding diagnostics into the admin workflow reduces operational risk and improves reliability over time.

Conversation orchestration

Define how conversations are managed throughout their lifecycle, not just at entry. Playbooks let admins set conditions based on customer context, wait time, and queue state, and trigger automatic actions without manual supervisor intervention. They are authored using guided templates in the admin center — no rules to write, no code to maintain. Built-in validation catches conflicts before anything goes live. These capabilities are available now in public preview: 

1. Dynamic prioritization: A playbook continuously monitors wait time and customer context. When conditions are met — for example, a premium customer waiting beyond a threshold with no senior agents available — their priority is automatically elevated. High-value and long-waiting customers rise to the top without anyone watching the queue. 

2. Overflow based on CSR availability: A playbook fires the moment a queue has no eligible agents. Based on customer segment, it transfers to a backup queue, offers a callback, or sends a graceful closing message. Every customer gets a response. None of them wait in silence. 

Key benefits 

With Service Operations Agent, organizations can: 

• Accelerate time to value by simplifying setup and onboarding 

• Reduce configuration errors through built-in validation and guidance 

• Improve operational reliability with proactive diagnostics 

• Lower dependency on specialized expertise with conversational experiences and templates for playbooks 

• Improve customer experience by automatically managing in-queue conversations — reducing wait times, preventing silent overflow, and ensuring high-value customers are prioritized without supervisor intervention 

• Continuously optimize contact center performance with ongoing insights 

Together, these capabilities establish a strong foundation for building, scaling, and managing modern contact centers. 

Looking ahead 

Service Operations Agent is part of a broader vision to bring agentic experiences for administrators in Dynamics 365 so we can assist them in their jobs to be done. Some of these are enhanced automation, better troubleshooting, simulated conversations for validating behavior and improved insights. For orchestrating conversations, we will provide capabilities to improve the in-queue lifecycle experience, such as re-connecting customers to their last customer service representative, handling overflows for direct-dial lines, out-of-hours queues, etc. Each new capability builds on the same playbook foundation — everything configured today carries forward as the platform grows.

All these additional exciting capabilities are soon to follow!

Learn more

• Public documentation for setup and diagnostics capabilities: Use Service Operations Agent in Dynamics 365 Contact Center (preview) | Microsoft Learn 

• Conversation orchestration capability: Configure conversation orchestration using AI-powered playbooks (preview) 

The post Introducing Service Operations Agent in Dynamics 365 Contact Center  appeared first on Microsoft Dynamics 365 Blog.

Modern customer experiences don’t live in a single system or interaction type. Whether agents resolve complex cases in Dynamics Customer Service or manage live conversations in Dynamics Contact Center, the quality of an interaction often depends on how the work is performed and not just what was said. 

Across both workloads, customers have consistently asked for the same missing capability: secure, structured visibility into the agent’s on‑screen workflow during customer interactions. Voice, chat, and transcripts capture part of the story, but they don’t always reveal how agents navigate systems, apply processes, or respond in real time. 

Today, Screen Recording in Dynamics 365 Customer Service and Dynamics 365 Contact Center addresses that gap by providing organizations with trusted, role‑based access to screen context that supports coaching, quality evaluation, and compliance. 

Why Screen Context Matters 

Customer interactions are rarely linear. Agents often work across multiple systems, reference internal knowledge, update records, and follow prescribed processes, all while engaging with the customer. 

Although Customer Service and Contact Center support different interaction models, customers using both workloads face remarkably similar challenges: 

• Supervisors need better context to evaluate agent’s activities when helping customers. 

• Compliance teams require auditable visibility in regulated environments. 

• Organizations want to coach agents more effectively without guesswork. 

Without screen context, organizations must infer intent and execution. With it, teams can: 

• Perform more accurate and objective quality evaluations 

• Identify training gaps and process inconsistencies 

• Reduce time to resolution by understanding workflow breakdowns 

• Validate compliance and required actions with confidence 

Screen recording complements existing call and chat records, enabling a more complete understanding of each interaction, regardless of the channel. 

One Capability, Designed for Two Workloads 

We’ve built Screen Recording in Dynamics 365 as a unified capability that serves both Customer Service and Contact Center, while adapting naturally to different ways agents work. 

Key Capabilities: 

1. Automatic Screen Recording for Call Conversations 

2. Manual Screen Recording for service reps working on multiple cases, chats, etc.  

3. All screen recordings are securely uploaded to Dataverse  

4. Role based access to both perform and access screen recordings 

Manual screen recording when service reps are working on cases, for example: 

To balance visibility with usability, recording is scoped intentionally, and configuration and operational details are managed by administrators.  

For step‑by‑step setup and configuration guidance, detailed documentation is available on Microsoft Learn. 

Secure by Design: Trust, Access, and Governance 

Because screen recordings may contain sensitive information, security and governance were foundational to the design. 

Access is controlled through role‑based permissions, ensuring only authorized users can record, review, or download recordings. Recordings are stored securely, with controls that align to enterprise and regulatory expectations. 

This approach allows organizations to unlock operational insight without compromising trust between agents, supervisors, and compliance teams. 

Learn More 

To explore how to configure and administer screen recording in your environment, visit the documentation on Microsoft Learn: 
https://learn.microsoft.com/en-us/dynamics365/contact-center/administer/configure-screen-recording 

We’re excited for you to try this capability and to hear how screen recording is helping you improve quality, coaching, and operational visibility across your service experiences. 

The post Bringing End‑to‑End Visibility to Customer Service and Contact Centers with Screen Recording in Dynamics 365  appeared first on Microsoft Dynamics 365 Blog.

Announcing new agentic customer experience capabilities in Dynamics 365 and Microsoft Copilot Studio across the entire customer lifecycle.

For years, customer experience (CX) leaders have navigated hard tradeoffs between better service and lower costs or faster resolution and deeper personalization, all while customer expectations continue to rise and teams are asked to do more with aging systems and flat headcount. Scaling growth meant scaling people. But that model has its limits.

What’s changed is agentic CX. AI can now move beyond simply assisting work to helping automate routine, predictable tasks throughout the customer journey. That shift frees teams to focus on the moments that require uniquely human skills including judgment, empathy, and creativity. And it has the opportunity to completely transform customer experience into a critical growth engine for organizations that adopt it now.

Today, we’re introducing real-time voice agents in Microsoft Copilot Studio and new agents in Dynamics 365 Contact Center, Dynamics 365 Sales, and Dynamics 365 Customer Insights.

Dynamics 365 Contact Center

Get started with real-time voice agents built with Copilot Studio

Contact us

New real-time voice agents in Microsoft Copilot Studio

Voice becomes even more critical in the era of AI to build trust and resolve complex high-stakes issues. According to research from Metrigy, “82% of all interactions use voice, either initially or as an escalation.“

We’re excited to announce the general availability of real-time voice agents in Copilot Studio, supporting the next generation of real-time voice models, extending traditional Interactive Voice Response (IVR) by using natural and flexible conversations with generative AI. Now, customers can simply talk like they normally would—without having to follow rigid pre-defined prompts. As customers move seamlessly between self-service and human support, the system carries context forward, so customers don’t need to repeat themselves.

Copilot Studio is Microsoft’s enterprise agent building platform allowing IT to build, manage, and deploy sophisticated custom agents. In addition to allowing customers to build custom agents, we’re bringing real-time voice capabilities to pre-built agents in Dynamics 365 Contact Center—available starting today.

Agentic contact center: Where customer intent drives action

Customers want a single, continuous conversation with the brands they love. Instead, they often experience fragmentation because AI in contact centers is often deployed as disconnected tools—self-service, agent assist, quality, and operations—leading to lost context and broken experiences.

Dynamics 365 Contact Center addresses this by treating the customer journey as a single, connected experience rather than a series of isolated moments. With the Customer Assist Agent, Quality Assurance Agent, and Service Operations Agent, AI spans the full contact center lifecycle, from self‑service and agent assistance to quality management and operational governance.

This isn’t about replacing our customer teams—it’s about allowing them to do what they do best: being there for customers when they really need them. By taking the drudgery out of back office work, agentic AI can recommend the next best action and do the heavy lifting behind the scenes, giving our teams more time to support customers and driving better outcomes for both customers and employees.

—Laura Mason, CEO, Legal & General Retail

Customer Assist Agent (generally available) manages high‑volume requests across voice and digital channels, carrying context through to resolution, including support for the real‑time voice agents discussed above and proactive communication. Real‑time voice agents, built and configured in Copilot Studio, support natural speech, interruptions, and multi‑language switching to help resolve common issues efficiently and in the way that customers prefer to communicate.

Quality Assurance Agent (generally available) continuously evaluates both AI and human interactions, tracking quality, sentiment, compliance, and resolution effectiveness in real-time, so supervisors can intervene earlier and coach their teams more effectively. Service Operations Agent (public preview) enables leaders to set up, configure, and optimize contact center operations through a guided, conversational experience without requiring deep technical expertise.

Together, these agents span the entire customer lifecycle, from self-service to operations, continuously learning from every interaction to deliver smarter, higher-quality customer experiences.

Agentic sales: Turning signals into momentum

Sales teams don’t lose deals because they lack data. They lose momentum managing it. Today, we’re introducing five new agentic features in Dynamics 365 Sales that automate routine work, keep data current, and proactively drive next best actions, keeping deals moving forward with greater speed and confidence.

Smarter signals give sales leaders a clearer, real-time view of the business so they can act sooner and drive opportunities forward. In complex deals, momentum often breaks when customer communications are scattered across emails, meetings, and documents, but Sales Opportunity Agent (generally available) acts as an AI deal brain synthesizing insights across Dynamics 365 and Microsoft 365 to surface risk early, flag shifts in engagement, and guide sellers to the next best actions without manual analysis or context switching.

Alongside it, new Operations Research (generally available for Premium customers) in Sales Research Agent (generally available) brings together pipeline, operational, and financial signals, so leaders walk into forecast calls with clarity on revenue health, risk, and confidence.

Two new agentic features that we’re announcing today are designed to increase seller productivity, help keep customer relationship management (CRM) data accurate, and move deals forward. Data Enrichment (generally available for Premium customers) and Recommended Actions (public preview for Premium customers) connect signal directly to action automatically keeping CRM fields like budget, contacts, and close dates up-to-date while surfacing the most impactful next step across leads, opportunities, and accounts right where sellers already work.

With Voice to CRM notes for Outlook and Microsoft 365 mobile applications (public preview), sellers can simply speak to capture updates, such as logging notes, updating opportunities, and surfacing what matters next—reducing manual effort while improving data quality and deal velocity wherever work happens.

AI‑driven data enrichment will improve the quality, consistency, and completeness of customer data in Dynamics, reducing administration for every person on the sales teams while improving our ability to action, analyze, and improve customer outcomes.

—Nick Segger, Head of Sales and Agency Transformation, NFU Mutual

Agentic customer insights: From campaigns to conversations

Conversational Journeys (generally available) in Dynamics 365 Customer Insights and Dynamics 365 Contact Center lets marketers, service reps, and sellers design multi-channel journeys that include AI-powered two-way conversations. Conversational Journeys is already available for phone interactions, and we are expanding this capability to SMS.

Now, the same continuity currently available in voice is extended to text for even more convenience to customers. Users can create AI agents that understand intent, adapt in real-time, and complete tasks end-to-end, stepping in with a human only when it truly matters. The result is simpler service resolution and more growth potential, with marketing teams able to drive action directly within a text whether it’s a reminder, a reorder, or a loyalty moment.

Get started with agentic CX: Real-time voice agents are available now

Ready to get started with these new agents? Connect with your Microsoft sales representative to explore upgrading to Premium or contact sales to learn more. For additional details, check out the Copilot Studio blog on real-time voice agents and our technical Dynamics 365 Contact Center blog, which dives deeper into the three new agents.

Note: Some of the capabilities described are in preview and subject to change. Customer examples are provided for illustrative purposes only. Results may vary. AI-generated insights should be reviewed by qualified personnel before action is taken.

The post Turning customer experience into a growth engine appeared first on Microsoft Dynamics 365 Blog.

For years, contact centers have shouldered some of the most persistent challenges in customer experience. They’re expected to help differentiate brands, improve customer retention, surface new revenue opportunities, and reduce frontline burnout — all while managing rising interaction volumes and escalating costs. Artificial intelligence has been positioned as the answer, and investment has accelerated accordingly. Yet despite rapid progress in AI capabilities, many contact centers still struggle to translate that innovation into durable, enterprise-scale impact.

The problem isn’t that AI doesn’t work. It’s that it has been applied in pieces. One solution for self-service. Another for agent assist. Separate tools for quality management, analytics, and administration. Each may deliver value in isolation, but together they create fragmentation. This creates disconnected experiences for customers, service representatives, supervisors, and administrators, and AI programs that stall at pilots rather than scaling across the business.

Addressing the challenge

Microsoft is addressing this challenge by rethinking how AI shows up across the entire contact center lifecycle. Instead of delivering disconnected features, Microsoft Dynamics 365 Contact Center introduces a coordinated agent model. Purpose-built AI agents are designed to work together from day one, each aligned to outcomes across engagement, quality, and operations. This approach directly contrasts with traditional CCaaS platforms. Typically, AI is embedded as isolated capabilities operating only within the boundaries of the contact center application, limiting reuse, shared context, and enterprise scale.

Built on a shared intelligence, data, analytics, and orchestration layer, these three contact center agents are designed to continuously learn from every interaction, whether resolved autonomously or with human support. Together, these agents help form the foundation of a truly modern contact center. Because they are built on Copilot Studio rather than a CCaaS-specific AI stack, Dynamics 365 Contact Center agents are not confined to a single vendor ecosystem. They can participate in broader business workflows with consistent governance, security, and learning across the enterprise.

Customer Assist Agent: Frontline for Every Customer Interaction

The Customer Assist Agent is the primary AI agent responsible for customer self-service across voice and digital channels in Dynamics 365 Contact Center.  

The newest capability in Customer Assist Agent is support for real-time voice AI. Real-time AI can listen, reason, and respond naturally with ultra-low latency. It handles interruptions, maintains context across turns, and adapts based on customer intent.

Traditional IVR can become brittle as interactions grow complex, while standalone AI voice solutions often lack enterprise control. Customer Assist Agent in Dynamics 365 Contact Center combines both. It uses deterministic logic for precise, auditable moments like payments and compliance, and generative, real-time reasoning for dynamic, multi-intent conversations. Built in Copilot Studio, real-time AI supports natural speech, interruptions, multi-language switching, and DTMF fallback. Connected to enterprise systems, voice becomes a resolution engine. Accuracy can improve over time as business users tune behavior directly in Copilot Studio using real interaction data.

When inquiries fall outside the bounds of automation or involve high-value or sensitive scenarios, the Customer Assist Agent escalates to a human Customer Service Representative (CSR). Importantly, this is not a handoff requiring customers to start over. The full conversation context, including intent, history, and progress, transfers intact so humans can pick up where it left off.

The Customer Assist Agent goes beyond inbound support by enabling proactive engagement—reaching out to customers on their preferred channels. AI agents use context, intent signals, and orchestration to initiate conversations for reminders, delivery updates, payment notifications, or issue resolution. Engagements range from simple notifications to dynamic, multi-step conversations that adapt based on customer responses across voice and digital channels.

Customer Assist Agent is Generally Available.

Quality Assurance Agent: Insight and Continuous Optimization

As AI becomes deeply embedded in customer interactions, quality management can no longer rely on sampling a small percentage of conversations after the fact. The Quality Assurance Agent supports supervisors in an AI and human collaborative model at scale, evaluating interactions in real time and post-conversation.

The Quality Assurance Agent is purpose-built to evaluate customer interactions with the Customer Assist Agent or customer service representatives at scale, in real time and post conversation. It measures conversation quality indicators such as empathy, tone, and business-defined custom quality criteria. Rather than producing static reports, it monitors for anomalies, emerging issues, and quality drops, surfacing alerts or recommended mitigation steps as needed. This is designed to help supervisors intervene earlier, address problems before they escalate, and maintain consistent service quality across both AI-led and human-led interactions.

Working in an autonomous loop with the Customer Assist Agent, the Quality Assurance Agent helps organizations identify opportunities to improve their self-service workflows and the overall quality of conversations.

Quality Assurance Agent is Generally Available.

Service Operations Agent: Accelerating Setup, Governance, and Scale

The Service Operations Agent is an AI assistant designed for contact center administrators and IT teams, focused on improving setup time, configuration, and governance. With more automation, operational complexity often increases. This means more environments to manage, more rules to govern, and more integrations to maintain. The Service Operations Agent can help administrators address this challenge.

Service Operations Agent helps provision and configure contact center environments rapidly, including trials and new deployments. It can potentially automate everything from initial environment setup to workflows and channels. This reduces manual effort and configuration errors, with the potential to significantly shorten time-to-value for new implementations.

The Service Operations Agent also introduces conversation orchestration. This continuously monitors and adapts customer conversations in real time using natural-language playbooks. It also helps improve queue management with capabilities such as dynamic prioritization of waiting conversations and intelligent overflow based on customer service representative availability.

Service Operations Agent is in Public Preview, available in US only.

“As one of the leading electronics retailers in Greece and Cyprus, we operate at scale across retail and after-sales service. Dynamics 365 helps us deliver a more proactive, conversational, and context-aware experience. With Customer Journeys and proactive engagement in D365 Customer Insights and autonomous conversation orchestration in Service Operations Agent for D365 Contact Center, we can anticipate customer needs, route customers intelligently, and carry interactions across SMS and voice, reducing friction and operational costs. At Kotsovolos, we continuously optimize our customer support to enable better living for everyone, everywhere.”

– Ioannis Papidis, CTO, Kotsovolos

Three Agents, One Copilot

Together, the Customer Assist Agent, Quality Assurance Agent, and Service Operations Agent can form the foundation of an autonomous, AI-powered contact center. Copilot ties them together, providing a single control plane where human leaders can oversee AI actions, guide learning, and maintain accountability. Each agent is priced using Copilot credits, providing flexible, usage-based economics.

Each agent is priced using Copilot credits, providing flexible, usage-based economics. Credits are used based on AI activity such as conversations handled, real-time assistance provided, summaries generated, and quality evaluations performed, rather than per-seat licensing. This allows organizations to start small, scale usage as adoption grows, and align spend directly to value delivered, while continuing to use the same agents across voice and digital channels. This outcome-based agent architecture is intended to replace disjointed tools and manual processes. It creates a coordinated system spanning engagement, quality, and operations.

The result is a blended workforce where humans and AI operate in concert, each focused on what they do best. AI handles scale, speed, and continuous optimization, while people deliver empathy, judgment, and trust. With Dynamics 365 Contact Center, Microsoft is defining a new model for customer engagement, one where AI is not an add-on but the connective tissue designed to enable faster resolution, smarter operations, and more meaningful customer relationships.

Learn more about Dynamics 365 Contact Center

Check out our latest announcement of new agentic customer experience capabilities in Dynamics 365 and Microsoft Copilot Studio.

The post Meet Your Agentic Contact Center appeared first on Microsoft Dynamics 365 Blog.