AI doesn’t just demand better processes. It requires a complete redesign of traditional healthcare operations for a new level of precision, traceability, and governance. A new operating model that the vast majority of healthcare organizations simply aren’t built around today.
Every week, another healthcare organization announces a major AI initiative. Ambient documentation. Automated prior authorizations. AI-assisted care coordination. The investments are real, the intentions are genuine, and yet, many of the results often still disappoint. A global 2025 McKinsey & Company survey found that most organizations struggle to scale AI beyond the initial pilot phase, and KLAS Research has repeatedly documented a persistent gap between AI adoption and measurable clinical or operational impact.
The commonly cited problem is that organizations are deploying AI into broken processes. The popular prescription is to fix the process first, then layer in the technology. That framing is understandable, but it’s also insufficient.
AI doesn’t just demand better processes. It requires a complete redesign of traditional healthcare operations for a new level of precision, traceability, and governance. A new operating model that the vast majority of healthcare organizations simply aren’t built around today.
Organizational intelligence is key, but often nowhere near AI-ready
Originally published: MedCity News