Healthcare
Building an AI Delivery Capability for a National Healthcare Organization
A national healthcare provider needed to move beyond isolated AI pilots toward a repeatable delivery capability, without compromising clinical governance or public trust.
-55%
Time-to-production
12+
Use cases under governance
2 quarters
Delivery capability stood up
The Challenge
- Multiple clinical AI pilots were running in parallel with no shared delivery standard or governance model
- Clinical and IT leadership had no common framework for evaluating which use cases were safe to scale
- Existing teams lacked the AI delivery and MLOps experience needed to operate pilots reliably in production
- Public and clinician trust depended on demonstrable, auditable governance
Our Approach
- Conducted an AI readiness assessment across clinical operations, data, and IT functions
- Designed an AI operating model anchored in a clinical AI governance board
- Assembled a project-based AI delivery team blending data engineers, MLOps specialists, and a clinical safety lead
- Built a repeatable delivery playbook so future use cases didn't require rebuilding governance from scratch
The Outcome
- Stood up a permanent AI delivery capability inside the organization within two quarters
- Reduced the time to move a clinical AI use case from pilot to production by more than half
- Established a governance model now used as the template for every new clinical AI initiative
- Built internal confidence among clinicians that AI recommendations were being properly governed