The pre-mortem on Epic Agent Factory asked who would answer when a health-system-built agent made a clinically significant error. It published on 9 June. I have since learned of a Becker’s Hospital Review report from 30 March confirming that one of America’s largest health systems had already been building those agents for weeks before the question was published.
It confirms the pre-mortem’s central argument. Neither the research nor the article surfaced how quickly the sequence had already begun.
The Deployment That Was Already In Motion
Advocate Health had already tapped Epic’s Agent Factory, becoming one of the first health systems to build and deploy agents through the platform. Andy Crowder, Advocate Health’s SVP and Chief Digital and AI Officer, described the direction in a LinkedIn post on 26 March: “By combining Epic’s Agent Factory Platform capabilities with Advocate Health’s scale, clinical insight, and commitment to innovation, we’re translating AI from promise into practice.” He pointed to a three-day Epic immersion at The Pearl innovation district in Charlotte, focused on speeding up pharmacy verification for complex medications and cutting infusion chart preparation time for pharmacists and nurses. Four working prototypes emerged, scheduled to go live in July 2026.
Crowder added: “Together, we’re advancing responsible, practical AI that fits naturally into clinical workflows, reduces friction, and gives clinicians back time to focus on what matters most.” It is a considered statement, and the commitment is genuine. But it is not a governance document. And Advocate Health is not unusual here. They are representative. They moved first because the platform enabled it, the commercial pressure to reduce administrative burden was real, and nothing in the regulatory landscape said stop.
This is the sequence the pre-mortem described. Capability arrived. Deployment followed. The governance architecture to surround it had not been ratified.
The Workflows That Come Next
Pharmacy verification and infusion chart preparation are not, in themselves, clinical decision-making. They reduce documentation burden and carry genuine operational value. But they are the entry point, not the ceiling.
Epic’s own Penny agent already handles prior authorisation for thousands of health systems. Agent Factory is the platform through which health systems build their own versions of exactly those capabilities. Prior authorisation sits at the intersection of clinical judgment and payer approval. An AI-generated argument that misrepresents a contraindication, omits a relevant diagnosis, or positions a clinical case in a way that leads a payer to deny appropriate care causes harm that is downstream and deniable. The agent did not make the clinical decision. But the agent shaped the argument that influenced it.
The pre-mortem’s central question, who owns the error, was always pointed at this trajectory. The agent is built by the health system, on Epic’s platform, using Curiosity’s foundation models, in a regulatory environment where no one has yet specified how liability is allocated between vendor and deployer. Advocate Health’s prototypes are the first step of a sequence that leads directly to that question.
Colorado Tried to Build the Rails
While health systems were building, legislators in Colorado were attempting to create the governance scaffolding that the platform lacks at a federal level. Three separate AI-related healthcare laws had been passed by June 2026, each addressing a different dimension of the problem, and each confirming the same underlying gap.
Colorado’s original AI Act, SB 24-205, was scrapped before it ever took effect. A legal challenge from X.AI in April 2026, supported by federal intervention from the DOJ, led to enforcement being suspended and the legislature repealing the law entirely. Its replacement, SB 26-189, was signed on 14 May. It is a narrower law, retaining consumer notice requirements and the right to meaningful human review following adverse outcomes, but dropping the duty-of-care standard and mandatory impact assessments that had made the original controversial. It takes effect January 1, 2027.
HB 26-1139, signed on 2 June, constrains how payers use AI in coverage determinations. It requires that AI-driven decisions be based on the patient’s individual medical and clinical history rather than group data, and that any denial or delay of coverage based on medical necessity receive review by a licensed clinician. It too takes effect January 1, 2027.
Together, SB 26-189 and HB 26-1139 create obligations on both sides of the prior authorisation workflow. Neither specifies who bears the cost when an agent-generated output leads to the wrong clinical outcome. Three laws confirming the gap exists is not the same as closing it.
The Sequence Is Not a Prediction. It Is a Pattern.
On 1 June 2026, eight days before the pre-mortem was published, the Joint Commission launched its first voluntary AI certification programme for healthcare organisations. Built on the initial guidance published with the Coalition for Health AI in September 2025, the certification covers governance, data management, risk and bias reduction, and monitoring. It is a meaningful step forward. But the certification recognises organisations, not individual tools. It does not validate or certify individual AI products. It contains no discussion of liability allocation. It is a framework for responsible intent, not a mechanism for accountability when something goes wrong.
Epic has not published a liability framework specifying what a health system owns when a self-built Agent Factory agent produces a clinical error. No Epic contract language or public terms of service document does so. No federal regulatory body has published guidance specifically addressing liability allocation for agentic AI operating within EHR environments. The FDA has authorised more than 1,400 AI-enabled devices and issued no specific enforcement guidance for agentic AI in EHR environments.
The pre-mortem’s conclusion was that if Epic published a clear liability framework and paired it with a safety review mechanism, Agent Factory could become the defining infrastructure layer of hospital AI over the next decade. That conclusion stands. What the evidence now confirms is that the clock is not running from some future launch date.
It was already running.