Every industry claims AI is transforming it. Healthcare might be the one where the gap between potential and reality is widest. Hospitals and clinics sit on enormous volumes of patient data. They run thousands of repetitive workflows daily. They face chronic staffing shortages with no relief in sight. On paper, healthcare is the perfect environment for AI to deliver immediate, measurable value. In practice, most of that value is still sitting on the table. The reason isn’t technology. It’s where the industry has been pointing it. The Diagnostic Obsession For the past decade, healthcare AI investment has disproportionately chased clinical applications. Image recognition for radiology. Predictive models for sepsis. Drug discovery pipelines. These are important problems, but they’re also the hardest to deploy at scale because they require regulatory approval, clinical validation, and physician trust that takes years to build. Meanwhile, the operational side of healthcare has barely been touched. The scheduling, the outreach, the…
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