Healthcare AI Is Absorbing Institutional Knowledge It Can't Actually Hold

Healthcare AI deployments are absorbing decades of clinical institutional knowledge from displaced human experts into systems with documented hallucination rates and no formal accountability frameworks. When experienced practitioners are removed from the loop, error-correction capacity drops precisely as AI failure modes, including confabulation and distributional shift, become most dangerous. Clinicians, hospital administrators, and regulators should treat this as a systemic risk, not an edge case. Unlike prior decision-support tools, these systems are now operating as primary knowledge repositories with no fallback.