3PillarsThree levers for AI in a health plan
Most plans point AI at the smallest lever. The bigger returns sit in the other two.
The office that actually pulls the levers
Naming the levers is easy. Pulling them is a question of structure.
Consolidate first, then deploy
A hundred workflow variants collapse into a handful, in the right order.
The forward-deployed health plan
Sort the org chart into volume and judgment, then staff to the second.
Most regional MA exits are not exits
Most "exits" are sales. Contract-level tracing tells them apart.
Reading the Cityblock-Homeward deal
The read the headlines missed, built from public CMS data in an afternoon.
The speed trap
Two versions of prior auth: one runs faster, one changes the work.
The moat inversion
When every buyer has the same models, your context becomes the moat.
The layer tax
Payer data arrives in layers. Each one caps what AI can return.
Every AI roadmap is secretly a data roadmap
The AI roadmap slips when the data roadmap under it was never written.
The talent auction
Regional plans cannot win the $600K talent auction. They do not need to.
The office agents report to
Agents that cross silos need an office that owns them.
Health plans already ran this experiment
VBC taught plans what happens when silos own the roadmap.
The $600K math
A credible AI hire costs $600K. The roadmap problem survives the hire.
You need a ledger, not a metric
Activity dashboards don't answer the board. A benefits ledger does.
Own the layer that stays
Route workloads across models. The context layer, locally hosted, is yours.
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