AI Readiness.
AI readiness in healthcare is decided long before the contract — in workflow design, governance, evidence standards, and the operating model that carries the tool through the first hard quarter.
The cost of a bad AI bet compounds inside the operating model.
Clinical AI, ambient documentation, and agentic tools are proliferating faster than the governance and adoption capacity around them. The temptation is to procure first and design later — producing pilots that don't scale and value stories the CFO can't defend.
AI must reduce burden, not create another screen.
A pre-procurement sequence.
- /01
Readiness
Honest assessment of where the organization is ready to absorb AI — and where it isn't.
- /02
Workflow fit
Map each use case to the clinical and operational day before it becomes a contract.
- /03
Governance & risk
Evidence bar, model oversight, escalation, and clinical accountability — designed once, applied across vendors.
- /04
Value framing
Define the outcomes that matter to clinicians, operators, and the board before the first pilot starts.
- /05
Pilot-to-scale
Design pilots that produce decisions, not artifacts — with a clear path to enterprise scale.
- /06
Adoption
Champion networks, reinforcement, and the human work that turns AI access into AI use.
What Changes.
- /01A smaller, sharper AI portfolio
- /02Governance that satisfies clinical, legal, and operational leaders
- /03Pilots that produce clear scale decisions
- /04AI use that holds across service lines and shift changes
Pressure-test your AI roadmap.
Bring us the portfolio, the live pilots, or the bet you're about to make.