Most healthcare AI stories start with diagnosis. Edmund Jackson thinks that misses the real bottleneck.

In this episode of The Tech Trek, Edmund Jackson, CEO and founder of Unity AI, joins Amir to talk about AI for healthcare operations. The conversation gets into why scheduling, staffing, follow up, payer coordination, and interoperability are often where healthcare breaks down, and why solving those operational problems may matter more than chasing the flashiest use cases.

Edmund brings a healthcare first view to AI. His argument is simple: healthcare is not slow because people are ignoring technology. It is slow because the real workflows are complex, regulated, high context, and hard to capture cleanly in software.

What You’ll Take Away

• Why healthcare experience matters when choosing which AI problems are actually worth solving

• Why diagnosis is not always the best starting point for healthcare AI

• How scheduling becomes much more complex when patients, payers, clinics, staff, protocols, and follow up all have to line up

• Why AI can help clinics save time while moving human staff toward higher value patient interactions

• Why interoperability is still hard, even with standards like FHIR gaining momentum

Timestamped Highlights

00:29, What Unity AI does and why healthcare operations is the focus

01:11, Why healthcare AI needs people who understand the domain, not just the technology

02:26, The danger of solving the hardest or flashiest problem instead of the most pragmatic one

05:15, Why AI may finally help healthcare handle personalization and operational complexity at scale

07:47, Why scheduling a healthcare visit is nothing like scheduling a delivery or restaurant order

10:42, How operational AI can save time and reduce downstream chaos in clinics

24:33, Why healthcare data is much harder to structure than financial data

One Line That Stuck

“Software is like children. Making it is all fun and games. Maintaining it is a whole other question.”

Practical Takeaways

• Start with the workflow that actually blocks progress, not the one that sounds most impressive

• In healthcare, operational context is often the product

• AI should create more room for humans to handle the interactions that require judgment, care, and clinical responsibility

• More software is not always the answer, especially in regulated environments where maintenance, compliance, and security matter

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