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:
https://www.microsoft.com/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.
