Insight
The gap between private-payer, market-driven healthcare (eg. the U.S.) and publicly funded, single-payor or universal models is widening - affecting both AI adoption and how its value is perceived. This divergence is driven by market dynamics, regulatory structures, and the differing incentives that shape innovation, access, and equity.
In the US (Market-driven)
- Shrinking coverage and fragmented deployment
- Rapid experimentation with limited systemic scaling
- AI incentive: Drive ROI, reduce labor cost, and differentiate care
In Single Payor / Universal systems
- Focus on closing care gaps and expanding provider capacity
- Centralized control, data sovereignty, and equity outcomes
- AI incentive: Support capacity, improve outcomes, and strengthen system resilience
Implications
Vendors & technology startups: AI products must align with each system’s incentive structure -emphasizing profitability and speed in the US, versus capacity, equity, and population outcomes in universal systems.