Charting a New Course
How organizations can transform agentic AI workflows into reliable, cost-efficient systems that consistently meet SLOs.
At Epicenter Health, (a fictional healthcare network), a quiet tension is playing out in exam rooms and on back-end servers. Dr. Reyes (the fictional Chief Medical Information Officer) has spent months championing the rollout of “clinical copilot” agents, those ambient AI helpers that listen to patient visits, transcribe conversations, suggest billing codes, and draft medical notes straight into the electronic health record (EHR). On paper, the program promised to relieve clinicians of tedious documentation and restore precious face-to-face time with patients.
But then came Jordan, a fictional patient managing a chronic condition with multiple specialists. During his routine appointment, his physician found herself waiting on the AI-generated note to catch up. The transcript lagged, the suggested coding was inconsistent, and the visit dragged on. Jordan left frustrated—sensing that technology was slowing his care rather than streamlining it. Dr. Reyes …