You're a Fixer (GTRA): You see broken systems and make them work. Healthcare is broken in very particular ways. The systems don't talk to each other. The workarounds are critical to patient safety. The "right way" doesn't actually work in practice, so people have built unofficial systems that do.
Healthcare AI is failing at a 60% deployment rate. That's not a typo. That's not "adoption challenges." That's failure. Systems that were implemented in real hospitals, with real data, on real patients, that didn't work.
Here's why: AI makes assumptions about data quality, system interoperability, and patient consistency that don't hold in healthcare. An algorithm trained on hospital A's data doesn't work on hospital B's data because hospital B built custom workarounds for things the algorithm doesn't know about. The legacy systems that have to integrate with the new AI were never designed to integrate with anything. The data people rely on to make decisions is inconsistent, has typos, was recorded in seven different formats by seven different people.
This is where you become invaluable. You see the gap between what the AI assumes about the system and what actually happens. You know where the workarounds are critical. You know which "wrong" processes can't be automated without breaking patient safety. You can tell a system implementer "yes, this looks right, but it will fail when..." because you've spent years watching systems fail and discovering why.
Your specific edge: You understand that systems don't fail because people are bad. They fail because the system requirements don't match reality. AI systems will fail for the same reason, and you'll see it coming. You'll know which failures matter (the kind that hurt patients) and which ones are just annoying (the kind that require a workaround).
The concrete play: Position yourself as the integration layer. You're the person who understands the existing system well enough to know what breaks when you add AI, and what doesn't. You're the person who can design the transition so the workarounds keep working. You're the person who catches the failure modes before they happen because you've seen every other failure mode.
This is where you shift from "fixing problems that happen" to "preventing problems that would happen." That's higher-leverage work, and it pays better.
"The healthcare AI that succeeds won't be the one with the best algorithm. It'll be the one with a Fixer who knows where the system is broken and makes sure the AI doesn't break it worse."