AdventHealth advances whole-person care with OpenAI

AdventHealth Deploys OpenAI to Reduce Clinician Workload

The AdventHealth hospital system is deploying OpenAI's ChatGPT for Healthcare across its enterprise to reduce administrative burden on its clinical and operational staff. By automating time-intensive documentation and support tasks, the organization reports an 80% reduction in time spent on certain administrative activities, allowing care teams to redirect their focus to patient interaction. The initiative aims to improve operational efficiency, expand clinical capacity, and shorten patient wait times for care.

A Strategy Focused on Adoption, Not Automation

Rather than pursuing isolated pilots, AdventHealth's leadership built its strategy around driving consistent and safe adoption of the technology. According to Chief AI Officer Rob Purinton, the organization treats adoption itself as the primary product, focusing on giving clinicians “time back” instead of framing the technology as automation. This approach required a structured rollout with measurable metrics, including tracking messages per user per business day as a key performance indicator. The choice of OpenAI's enterprise tools was based on their reasoning capabilities, structured outputs, and governance controls suitable for a regulated healthcare environment.

Key elements of AdventHealth's implementation strategy include:

• Measuring adoption as a primary operational metric, managed like any other KPI.
• Using domain-based peer groups (e.g., finance teams training finance teams) to scale usage with relevant best practices.
• Leveraging system-level data, such as timestamps in electronic health records, for objective workflow performance measurement.
• Deploying enterprise-grade tools like ChatGPT for Healthcare to meet privacy and compliance requirements.

The Impact on Workflows and Future Direction

In one of the first major use cases, physician advisors in utilization management used ChatGPT for Healthcare to cut the time spent assembling case information from 10 minutes to two, while maintaining quality. Similar efficiencies are being reported across HR, finance, and IT for tasks like drafting documents and summarizing notes. For AdventHealth, these time savings represent reclaimed capacity that can be reinvested into higher-value work and direct patient care. The organization views these initial gains as a foundation for broader applications in patient access and clinical decision support, proving that successful AI scaling in a complex enterprise depends more on change management and trust than on the technology alone. As Purinton notes, “Adoption is not ‘go use the product.’ It’s ‘change leadership.’”

AdventHealth's experience demonstrates that for large enterprises, the primary challenge of AI implementation is not technological but operational, requiring a deliberate strategy that treats user adoption and workflow integration as the core product to be measured and managed.