Today, we stand at the dawn of a new era—defined by autonomous AI agents in Dynamics 365. Microsoft’s Release Wave 2 signals a revolutionary shift from incremental feature updates to truly intelligent, agent-orchestrated systems.

If you’re exploring early access or prepping for October’s general availability, here’s everything your team needs to know about building, implementing, and scaling autonomous AI agents with Dynamics 365.

The Autonomous AI Agents in Dynamics 365

Forget incremental progress, with the 2025 wave, Microsoft is turning business apps into swarms of AI agents that:

• Execute complex, multi-step processes independently
• Make contextual decisions using real-time data
• Learn and adapt from historic patterns
• Collaborate with other agents for multi-agent orchestration

Key Autonomous Agents in Release Wave 2

Here are some of the most significant agents available now or soon:

Dynamics 365 Sales Agents

• Sales Qualification Agent: Research, draft emails, qualify leads, and autonomously engage prospects.
• Sales Order Agent: Automates orders, streamlines customer communications.

Customer Service & Contact Centre Agents

• Case Management Agent: Creates and manages cases from customer interactions, wraps up resolutions.
• Customer Intent Agent: Analyses context, builds intent libraries for smarter service.
• Knowledge Management Agent: Resolves issues, generates knowledge articles.
• Customer Feedback Agent: Monitors sentiment, deploys satisfaction surveys.

Finance Agents

• Account Reconciliation Agent: Matches transactions, learns, and suggests corrections for exception handling.
• Financial Reconciliation Agent: Cleanses data, automates reporting, manages exceptions.

Supply Chain & Operations Agents

• Supplier Communications Agent: Autonomous relationship management, proactive disruption prevention.
• Time and Expense Agent: Automates entry, tracking, approvals, and invoicing.

Implementation Phases

1. Environment Setup: Enable early access, configure security and Azure, establish governance.
2. Agent Configuration: Define business rules, connect data, trigger orchestration, build approval workflows.
3. Testing & Validation: Sandbox trials, user acceptance, performance monitoring, and gradual rollout planning.

Business Impact & ROI

The results speak for themselves:

• Operational Efficiency: 25% gains reported in core processes.
• Finance: 50% faster month-end close.
• Manufacturing: 85% reduction in downtime.

Industry projections estimate 15% of daily business decisions will be agent-driven by 2028, with an economic impact of $22.3 trillion globally by 2030.

Advanced Features & Capabilities

• Multi-Agent Systems: Teams of agents collaborate, delegate, and share context for seamless end-to-end automation.
• Autonomous Triggers: Agents activate on real-time events, schedules, or exceptions.
• Learning & Adaptation: Agents improve continuously from historical data and user corrections.

Implementation Best Practices

• Strategic Planning: Assess processes, ensure data quality, define KPIs, and manage organisational change.
• Phased Strategy: Start internally, scale after demonstrating ROI and driving user adoption.
• Technical Considerations: Maintain continuous data quality, optimise agents, and integrate API strategies.

Conclusion

2025 marks a turning point where autonomous AI agents move from concept to core business asset, enabling organisations to operate faster, smarter, and with more agility than ever before. 

At Osmosys, we’re excited to help you unlock the power of these agents—whether you’re ready to start your early access journey or planning for long-term ROI.

Ready to build your constellation of agents? Talk to our experts and be at the forefront of agentic business transformation.