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Building the foundation for agentic AI in healthcare

What happened
Based on Microsoft Source · Aug 11, 2026

Three health systems implemented Microsoft’s agentic AI tools to address clinician burden, data fragmentation, and infrastructure reliability, reporting measurable improvements in patient flow, operational efficiency, and system resilience.

Building the foundation for agentic AI in healthcare
Microsoft Source — Microsoft
Key points
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Grounded in trusted data, embedded in the workflow, and running on always-on infrastructure.
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It’s Tuesday morning, and the hospital is already behind in ways it won’t recover by the end of the shift.
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A physician is 10 patients in and hasn’t finished a single note, caught in the constant tug-of-war between the patient in front of her and documenting the one she just left.
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Two floors up, a nurse is several hours into a 12-hour shift and has spent more of it at a workstation than at a bedside.
Key numbers
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This shift enabled real-time data exploration and faster decision-making, leading to measurable improvements in emergency department and inpatient flow metrics between January and March 2026, including a 43% reduction in inpatient bed wait...
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The migration reduced downtime costs, improved system reliability, and enabled disaster recovery failovers in under 30 minutes.

Healthcare organizations face daily operational challenges such as clinician burnout, fragmented data systems, and unreliable infrastructure, which disrupt workflows and delay patient care. Microsoft’s agentic AI solutions aim to address these issues by integrating trusted data, embedding agents into existing workflows, and leveraging enterprise-grade infrastructure. The approach emphasizes coordination over isolated tools, enabling real-time decision-making and scalable automation across clinical and operational domains.

Brown University Health deployed Dragon Copilot, an AI clinical assistant, to reduce documentation burden and cognitive load for clinicians, allowing them to focus more on patient care. The health system also built emergency department agents to streamline policy inquiries and specialist directory access, while rolling out Microsoft 365 Copilot organization-wide for tasks like inbox management and contract analysis. These initiatives contributed to faster policy development and improved operational efficiency.

Peterborough Regional Health Centre (PRHC) prioritized data consolidation by migrating 18 production systems to Microsoft Fabric, creating a single source of truth for analytics and AI. This shift enabled real-time data exploration and faster decision-making, leading to measurable improvements in emergency department and inpatient flow metrics between January and March 2026, including a 43% reduction in inpatient bed wait times and a 70% decrease in ambulance offload times.

Franciscan Health migrated its Epic EHR to Azure to enhance performance, scalability, and disaster recovery, ensuring uninterrupted access to critical clinical data. The migration reduced downtime costs, improved system reliability, and enabled disaster recovery failovers in under 30 minutes. By leveraging a single-vendor platform, Franciscan simplified the integration of future AI agents and workloads, demonstrating how resilient infrastructure underpins coordinated action and better patient outcomes.

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