AI pilot purgatory: why so few clinical AI pilots ever scale

Every health system we spoke to this year has a clinical AI pilot. Very few have a second deployment. The reasons are rarely about model accuracy.

The pattern is consistent: the pilot was owned by an innovation team, not by the service line that would carry the cost. Integration was budgeted as a one-off rather than as a recurring line. And the success measure was accuracy against a benchmark instead of a change in an operational number the CFO already tracks.

The systems that scaled did three things differently. They named an operational owner before the pilot began, they agreed the success metric with finance, and they priced integration as part of the contract. None of this is technical. All of it is decided in the first month.