61% of medical technology firms report using AI for medical imaging and 57% of pharmaceutical and biotech firms use it for drug discovery, the two clearest AI adoption successes in healthcare. But the same 2026 survey data shows only about 5% of enterprise AI pilots across industries, healthcare included, actually reach production deployment.
The uneven pattern makes sense once you look at what imaging and drug discovery share: both are well-defined technical problems with clear success metrics and large, structured datasets, exactly the conditions where current AI performs best. The much harder, messier work of integrating AI into actual clinical and administrative workflows, where more than half of health IT leaders cite infrastructure and data governance as the real barrier, has not seen anywhere near the same adoption curve.