Treat Adoption as the Product
AdventHealth’s strategy for scaling AI across a large, multi-state health system centers on the philosophy that adoption is the primary outcome, not just a byproduct of deployment. Rather than running isolated, experimental pilots, leadership framed AI as a tool to reclaim time for clinicians and staff. By positioning the technology as a way to reduce administrative burden—specifically targeting "pajama time" (after-hours documentation)—the organization successfully moved employees from the sidelines to active, consistent usage.
Measuring Impact Through Operational KPIs
To ensure accountability and demonstrate value, AdventHealth manages AI usage with the same rigor as any other business KPI. Key strategies include:
- Quantifiable Metrics: Instead of relying on self-reported surveys, the team tracks system-level data like messages per user per business day and time-per-task improvements within electronic health records.
- Domain-Based Peer Groups: To drive adoption, the organization avoids centralized, generic training. Instead, they facilitate peer-to-peer sharing where finance teams, HR, and clinical staff share prompts and workflows tailored to their specific functional needs.
- Workflow Integration: The focus is on "time back." For example, in utilization management, AI generates structured summaries and drafts rationales, reducing a 10-minute manual review process to significantly less time, while keeping the human clinician in the loop for final judgment.
Infrastructure for Enterprise Scale
AdventHealth selected OpenAI’s enterprise offerings to meet strict healthcare requirements for privacy, governance, and reliability. The decision was driven by the need for robust reasoning capabilities and structured outputs that could be safely scaled across a complex, regulated environment. By moving beyond simple productivity software to enterprise-grade infrastructure, the organization has established a foundation for future applications in patient access and clinical decision support.