Contact centers are under more pressure than they've been in years. Interaction volumes keep going up while budgets and headcount stay flat. AI has helped take some of that load off, and most service teams have already rolled it out in some form — a chatbot for common questions, an upgraded IVR, a copilot that helps reps during calls, a separate tool that scores conversation quality. The problem is that each of these tools usually run on their own, with no real connection between them. The bot doesn't see what the IVR picked up, and the QA tool can't reference what the copilot suggested mid-call. The customer feels this disconnect the most. They end up repeating themselves every time the conversation moves between channels.
A Gartner survey shows how widespread this gap is: 73% of people start their service journey in self-service, but only 14% of issues are fully resolved there. The rest bounce back via other channels or get handed off to a human rep with little context to pick up from. For service leaders, the work now is less about adopting AI and more about getting the pieces to work together. That's the shift Microsoft is making with Dynamics 365 Contact Center.
AI agents in Microsoft Dynamics 365 Contact Center
Dynamics 365 Contact Center comes with five pre-built AI agents i.e. Customer Assist, Customer Intent, Customer Knowledge Management, Quality Assurance, and Service Operations, plus the option to build custom ones on Copilot Studio. All of them sit on a shared data and orchestration layer, so they pass context to each other instead of working as separate tools.
That changes how the work flows. When a self-service conversation escalates, the rep picks up with the customer's intent already understood. When a case closes, the knowledge article it generates is the same one the next self-service customer will see, so improvements compound instead of staying locked inside one tool. And because custom agents plug into the same data and orchestration layer the pre-built ones use, teams can extend the stack for industry-specific workflows without creating a parallel system.
Pricing for these agents is on a pay-as-you-go basis through Copilot credits, so teams can start small and scale as adoption grows.
Let’s dive into what each agent does.
Customer Assist Agent
Status: Generally Available
Customer Assist Agent is the frontline AI for self-service across voice and digital channels. It holds real-time conversations — handling interruptions, switching languages mid-call, and picking up on multi-intent queries — and hands off to a human rep with full context when escalation is needed.
- Real-time voice AI with natural speech and low latency
- Multi-language switching and keypad input fallback
- Mix of rule-based logic for compliance-sensitive moments and generative reasoning for open-ended conversations
- Full conversation context transfers on escalation
Customer Intent Agent
Status: Generally Available
Customer Intent Agent figures out why customers are reaching out by analyzing past cases and live conversations. It builds an intent library that updates itself as new interactions come in, so service teams aren't manually rewriting bot menus every quarter.
- Auto-discovers intents from historic and current data
- Powers both self-service flows and rep-assisted chats from the same library
- Surfaces intent-based prompts in the Copilot pane for reps
- Continuously updates with no manual maintenance
Customer Knowledge Management Agent
Status: Generally Available
Customer Knowledge Management Agent generates and maintains knowledge articles from real cases, conversations, and emails. After a case closes, it analyzes the resolution, checks for existing articles, fills gaps, and routes drafts to an admin for review before anything goes live.
- Auto-drafts articles from case notes, transcripts, and emails
- Checks for duplicates before creating new entries
- Routes to administrators for approval
- Publishes approved articles into self-service flows and IVRs
Quality Assurance Agent
Status: Generally Available
Quality Assurance Agent scores customer interactions across both AI and human reps, in real time and after the conversation ends. It replaces the old model of sampling a few calls a month with continuous evaluation across the full volume.
- Real-time and post-conversation scoring
- Measures empathy, tone, compliance, and resolution against custom criteria
- Alerts supervisors to anomalies and quality drops as they happen
- Email evaluations available in public preview
Service Operations Agent
Status: Public Preview — US only
Service Operations Agent is built for contact center administrators and IT teams. It speeds up environment setup, automates configuration, and adds conversation orchestration through natural-language playbooks that monitor and adapt live conversations.
- Faster setup for new environments and trials
- Natural-language playbooks for live conversation orchestration
- Dynamic queue prioritization
- Intelligent overflow routing based on rep availability
Custom Agents
Available via Copilot Studio
For workflows the first-party agents don't cover, Copilot Studio lets teams build their own. Custom agents plug into the same intent library and knowledge base the out-of-box agents use, so they extend the stack rather than fragment it.
- Built low-code or no-code in Copilot Studio
- Share data and orchestration with first-party agents
- Tailored to industry workflows or internal processes
- Same governance and security model
Real-world ROI of AI agents in Dynamics 365 Contact Center
The earliest benchmarks on impact of AI agents in Dynamics 365 Contact Center come from Microsoft's own service organization running on the platform, and Forrester TEI studies commissioned to measure the broader Customer Service impact.
Microsoft's Copilot deployment results in Customer Service and Support
Microsoft's Customer Service and Support organization migrated to Copilot-powered service in 2024 and reported clear operational gains:
- 12% decrease in chat average handle time
- 13% fewer agents needing peer assistance to resolve cases
- 31% increase in first-call resolution
- 20% reduction in misrouted calls
Forrester TEI: 315% ROI for Dynamics 365 Customer Service
Most of the AI agents in Dynamics 365 Contact Center — including Customer Intent, Customer Knowledge Management, and Quality Assurance — are shared with Dynamics 365 Customer Service. A Forrester TEI study commissioned by Microsoft modeled the impact of Dynamics 365 Customer Service for a composite organization:
- 315% ROI over three years
- Payback in under six months
- $14.7 million in financial benefits over three years against $3.54 million invested
Forrester TEI: $2.7M projected NPV for Dynamics 365 Contact Center with Teams Phone
A separate 2025 Forrester TEI study commissioned by Microsoft modeled the projected impact of unifying Dynamics 365 Contact Center with Microsoft Teams Phone:
- Up to $2.7 million in net present value over three years
- $3.5 million in projected benefits across the same period
- Up to 55% less telephony downtime, equivalent to 74,000+ rep-hours saved
What customer service leaders should weigh before scaling AI adoption in Dynamics 365 Contact Center
Scaling AI agents in a contact center involves more than turning the technology on. The deployments that move past pilot stage tend to share a handful of practical conditions on the ground — the kind that don't always show up in a vendor demo but end up determining whether the rollout actually delivers value over time. Here are five worth assessing early.
- Voice handling under live conditions - Production calls bring interruptions, accents, background noise, and mid-call topic shifts. The voice AI needs to handle all of that consistently across thousands of live conversations, not just in scripted demos.
- Context preservation on handoff - When AI escalates a conversation, the rep should pick up with everything the customer already shared. If the handoff drops context and the customer ends up repeating themselves, the deflection number on paper won't translate into real efficiency gains.
- Continuous quality monitoring across AI and human interactions - AI behavior can drift as new intents emerge or knowledge gets updated. Continuous evaluation across both AI and human conversations catches problems before customers start complaining about them.
- Change management and rep adoption - AI tools only deliver value when frontline reps actually use them in their daily workflow. That means involving the people who handle live conversations in how the tools get configured, and giving them clear feedback channels to flag what's not working in practice.
- Integration with the broader Microsoft estate - Customer Insights, Dataverse, Power Platform, and Microsoft 365 all hold customer context that's useful in the contact center. AI agents should be able to draw on that data natively, without manual stitching between systems.
Most customer service leaders evaluating Dynamics 365 Contact Center are past the question of whether to adopt AI agents. The harder work is sequencing the rollout so the AI delivers measurable value across self-service, quality, and operations — and that's where most pilots stall.
At Alletec, we work with both; the teams already running Dynamics 365 who want to scale AI thoughtfully and teams evaluating the move for the first time. If either describes where you are, we'd be glad to talk through what we've seen working in similar service environments.
Looking to scale AI agents in Dynamics 365 Contact Center or just starting to evaluate the move? Connect with our team →
