Dynamics 365 Contact Center: Copilot and AI innovation – Use agentic simulations to evaluate contact center setup

Agentic simulations are an AI-driven capability of Service Operations Agent that enable organizations to evaluate how their contact center behaves under realistic customer conditions before those conditions occur in production. Administrators define simulation scenarios using natural-language prompts. Agentic simulations then generate realistic synthetic conversations, runs them end-to-end through the configured contact center, and calculates the contact center KPIs. What problems it helps solve Readiness of self-service experiences: Assess how AI agents handle real customer intents, variations in behavior, and edge cases. Effectiveness of assisted service flows: Validate routing, assignment logic, and service representative experience in human-assisted scenarios. Confidence in scale and load readiness: Understand how configurations and operations perform under realistic volume and fix any reliability and latency issues. Preparedness of service representatives: Enable safe practice and evaluation using realistic customer interactions without impacting live customers. Key capabilities Natural-language prompt interface for defining simulation scenarios Simulation of varied customer intents, personas, and behaviors End-to-end execution across AI agents, routing, and configurations Out-of-the-box KPI dashboards and scorecards Reusable and saved prompts, including canned scenarios Safe, pre-production execution with no impact on live customers Agentic simulations are currently available for the voice channel in the English language only. They support flows without Dual-Tone Multi-Frequency (DTMF)-based menu interactions and up to five conversations in a simulation. Business Value: Every contact center decision, such as deploying an AI agent, adjusting routing, onboarding new staff, or preparing for higher volumes, ultimately answers the same question: “Will this work as expected when real customers arrive?” Agentic simulations provide a clear, data-backed answer before changes reach production. By generating realistic customer conversations and running them end-to-end through the contact center, organizations can see how their self-service, assisted service, and operational setup behave under real-world conditions. Instead of relying on assumptions, limited testing, or post-go-live corrections, teams gain measurable insight into experience quality, readiness, and scale. This feature transforms how contact centers operate: Experience quality improves because AI agents and service representatives are evaluated against realistic scenarios. Operational risk decreases because configuration and routing issues are identified early. Time to value accelerates because onboarding, training, and change validation […]

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