A physician orders cancer treatment. The delay isn't clinical; it's a prior authorization taking days. This normalized inefficiency plagues healthcare, with AI pilots failing to break the logjam. The fundamental barrier isn't technology, but trust, which in healthcare, is a data problem. According to Snowflake, achieving trustworthy AI healthcare requires more than just algorithms; it starts with the data itself.
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Trustworthy AI is an architectural necessity built on three pillars: transparency, ensuring every decision is traceable; human-in-the-loop, reserving complex judgment for clinicians; and built-in governance, making compliance with regulations like HIPAA a prerequisite, not an afterthought.