AI governance is not post-deployment oversight. Build data authority, identity, security, evidence and bounded agent controls into the architecture before production AI scales risk.
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Prepared as follow up to our previous article, The AI Agent Graveyard. We argue both sides of the agentic AI debate — the compounding-error case against it and the architectural case for it — then lay out the reference architecture, autonomy model, and governance controls that separate agents that die at month eighteen from agents that run the business.
Most healthcare AI pilots fail within 18 months — not from bad algorithms, but from missing governance, auditability, and deployment discipline. Inside the three silent killers and how to build AI that survives production.
Healthcare has never lacked data — it has lacked togetherness. A candid look at why unification is hard, what it makes possible, and how to pursue it without amplifying risk in the age of agentic AI.