AI In Healthcare 2026: The System May Be Broken. Let’s Try To Fix It
✨ AI Summary
🔊 جاري الاستماع
InnovationAI In Healthcare 2026: The System May Be Broken. Let’s Try To Fix ItByPaul Kovalenko,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)May 29, 2026, 06:00am EDTPaul Kovalenko, Langate CTO, SaaS Consultant. Helping enterprise SaaS companies optimize their development costs. gettyHealthcare isn’t broken where people think it is. It’s not a lack of intelligence. Not a lack of expertise. Not even a lack of effort. Clinicians, researchers and operators are making the right decisions every day under immense pressure. The real issue sits deeper in the system that those decisions depend on. Care is fragmented across tools, teams and timelines. Information exists, but not where or when it’s needed. Workflows are designed around processes, not outcomes. And execution often fails not because the decision was wrong, but because the system couldn’t carry it through. From a CTO’s perspective, the real challenge isn’t better decisions. It’s rebuilding the system on which those decisions depend. What’s Actually Broken (And Why It’s Not Obvious) Diagnosis is not the bottleneck. In most modern healthcare environments, clinicians can accurately identify problems. The issue is what happens next. Orders get delayed. Data arrives too late. Follow-ups slip through cracks. Care plans fragment among departments. Operational friction becomes the invisible force molding outcomes. These failures rarely show up in dashboards. They don’t look like errors. They look similar to delays, misalignments and shortcomings. But collectively, they define patient experience, cost and clinical quality. Healthcare doesn’t fail because people don’t know what to do. It fails because systems can’t coordinate what needs to happen. Healthcare fails in coordination, not capability. Yet most innovation still targets the wrong layer. Why AI Deployments Keep Mi...
