The Biggest Challenge in AI Healthcare Isn't AI

Most discussions around AI healthcare focus on models, agents, and automation.

I think the real challenge is interoperability.

AI systems need clean, structured data. Healthcare systems often provide the opposite: fragmented records spread across hospitals, labs, insurers, and legacy software.

This is why standards such as HL7 and FHIR have become increasingly important. They create a common language that allows healthcare applications and AI systems to exchange information reliably.

What's interesting is that many organizations working in healthcare technology—including Epic, Oracle Health, Microsoft, Google Cloud, and implementation-focused teams such as GeekyAnts—are investing heavily in interoperability rather than treating it as a secondary concern.

My opinion is simple:

FHIR-first architecture is becoming a prerequisite for scalable healthcare AI.

Without it, many AI projects risk becoming impressive demos that never successfully reach production.

How are other developers approaching healthcare interoperability today?