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Healthcare AI Is Solving the Wrong Problem, and We’re Calling It Progress
Billions of dollars have flowed into healthcare AI over the last decade, and the results are, by many conventional measures, impressive. Documentation is cleaner. Billing cycles are shorter. Administrative throughput has never been more efficient. But a more important question still lingers. Why does the patient experience still feel so utterly fragmented and reactive? It’s because we built the machine for the institution, not the person. Healthcare AI is serving reimbursement cycles, compliance frameworks, and operational throughput. But these are metrics that serve the system’s financial architecture, not the human being inside it. They don’t compensate for the lack of care. Incentives shape outcomes, and right now, those incentives are misaligned with what it actually means for a person to get better. Speed has become a proxy for progress, but it’s hardly doing any justice to the meaning of advancement. While it is easy to measure, when applied to a flawed system, it only accelerates the flaws. Automating inefficiency at scale does not transform care, but reinforces the very structures that limit it. I keep coming back to the data. More than 80% of ph...
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