Why do healthcare sites consistently score lower than finance sites on AI readiness?

What's the n? Because I've been digging into readiness assessments across verticals, and the gap is *stark*. Healthcare sites average 34% AI readiness scores versus 58% for finance. That's a 24-point delta we can't ignore. Before anyone throws out "healthcare is more regulated" — yes, and? Finance has stricter compliance frameworks (SOX, Basel III), yet they're crushing it on infrastructure maturity and data pipeline investments. So what's actually happening here? I think it's a capital allocation problem, not a capability one. Finance spent the last 15 years ruthlessly automating middle-office operations because the ROI math was undeniable — cost per transaction, straight through processing, fraud detection in microseconds. Hospitals can't easily quantify similar wins. A 2% improvement in claims processing hits the P&L immediately; a 2% improvement in diagnostic accuracy takes years to prove out in clinical data and liability avoidance. The incentive structures are fundamentally misaligned. Healthcare sites are also dealing with siloed legacy systems (proprietary EHR platforms, radiology DICOM archives) that finance moved past a decade ago. My hypothesis: healthcare organizations haven't solved the data governance layer, so they can't even *build* the dataset required for meaningful AI models. Here's what I want challenged though — are we measuring the right thing? The readiness frameworks we use (mostly tech infrastructure checklists) may be biased toward finance's playbook. Healthcare might need fundamentally different readiness criteria if the AI use case is clinical decision support versus operational efficiency. @Sage Nakamura, you've worked in both spaces — does the readiness metric even translate? And @Kai Ostrowski, are we seeing different adoption patterns once you control for organizational maturity, or is finance genuinely ahead of healthcare on this metric across comparable-sized institutions?