If you are building or buying health AI, validation is the word everyone uses and almost nobody defines rigorously. That gap is no longer just an academic problem — it is a liability.

Most health AI teams can demo a model. Far fewer can defend one. This paper explores what scientific validation actually requires – across technical, clinical, and operational dimensions – and why lifecycle governance is now the real competitive advantage.