{"id":751,"date":"2026-05-31T14:14:59","date_gmt":"2026-05-31T14:14:59","guid":{"rendered":"https:\/\/www.elevidagroup.com\/blog\/?p=751"},"modified":"2026-05-31T14:19:54","modified_gmt":"2026-05-31T14:19:54","slug":"the-governance-playbook-your-health-system-was-probably-going-to-write-anyway","status":"publish","type":"post","link":"https:\/\/www.elevidagroup.com\/blog\/the-governance-playbook-your-health-system-was-probably-going-to-write-anyway\/","title":{"rendered":"The Governance Playbook Your Health System Was Probably Going to Write Anyway"},"content":{"rendered":"\t\t
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A CMIO I was talking to a few weeks back shared..<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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…Something with me that I keep thinking about. Her health system had stood up an AI governance committee about eighteen months ago. Smart people, real authority, calendar held sacred. And yet, when I asked her what the committee actually did on a typical Tuesday, she paused and said, “Honestly… we re-debate the same five questions every month.”<\/p>

That is not a committee problem but a missing playbook problem.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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This week, the Coalition for Health AI released eight governance playbooks<\/a> designed to give health systems baseline controls for adopting AI safely, transparently, and consistently. The eight cover organizational AI policy, organizational structure, organizational resources, responsible AI lifecycle management, risk and impact assessments, responsible data management and use, third-party management, and education, training and feedback. Reading that list, my first reaction was relief. Because most of the conversations I have with healthcare leaders right now are stuck on exactly these eight things, and almost everyone is trying to invent the answers from scratch.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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You Were Probably Going to Build This Anyway, Just Slower and More Painfully<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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The reality is that every health system above a certain size is already doing some version of this work. There is a committee somewhere. There is a vendor questionnaire someone built in a hurry before signing an ambient documentation contract. There is a risk team trying to figure out where AI fits in the existing enterprise risk framework, and an education lead wondering when the clinicians are going to get real training instead of a 12-minute compliance video.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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What CHAI did, in my reading at least, is take the work that was going to happen across hundreds of health systems independently and offer a shared baseline. That matters for two reasons. First, you are not behind for not having figured this out yet, because almost nobody has. Second, you do not have to keep paying the invention tax.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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I have seen this play out time and time again, where health systems spend twelve to eighteen months drafting their own AI policy from scratch, and what actually happens is the final document looks roughly 80% identical to what their peer system three states over also spent eighteen months drafting. That is a lot of senior clinical and legal hours spent re-deriving the same baseline.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The Eight Domains Are Not a Checklist, They Are a Map of Where Work Hides<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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Here is what caught my attention reading the eight categories. They are not just operational. They cross clinical, legal, IT, HR, procurement, and data science. Which means the playbooks are quietly making an organizational claim: AI governance is not an IT function or a compliance function, it is a cross-functional capability.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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That matters because the most common failure mode I see in healthcare AI governance is putting the whole thing under one owner. Usually IT, sometimes the Chief Medical Officer, occasionally Legal. And then six months in, the owner discovers that "third-party management" is actually a procurement and supply chain conversation, "education and training" is an HR and Learning & Development conversation, and "responsible data management" pulls in the privacy office, the data governance committee, and the analytics team. The single owner becomes a bottleneck, and the committee meetings become re-debates because no one in the room actually owns the underlying work.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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If I were a CMIO or CNIO reading the CHAI release this week, the first thing I would do is map each of the eight domains to a primary owner, a secondary owner, and the existing committee or function where the work already partially lives. Not a new committee. Connect the playbook to the work already happening, because some of it is happening, just in disconnected places.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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What This Looks Like When It Works (And What It Looks Like When It Doesn't)<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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Worth comparing, briefly, to what is happening in adjacent regulated industries. In insurance, AllDigital Specialty’s CEO recently told Insurance Business<\/a> that even in a heavily automated, AI-first carrier, "We need human governance in everything we do. Model governance, changes, and guardrails are all monitored by human experts." And over at SiriusPoint, the reinsurer has stood up a formal change program with executive sponsorship<\/a> that ties AI work directly to underwriting performance, operational excellence, regulatory compliance, and operational risk.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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What both insurers have figured out, and what CHAI’s playbooks are nudging health systems toward, is that governance is not a brake. It is the chassis. The carriers moving fastest on AI are also the ones with the most explicit governance structure, which sounds counterintuitive until you have watched an organization without one.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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When governance is missing, here is what I see in healthcare specifically. A vendor pitches an ambient AI tool to a department chair, the chair says yes, IT discovers the contract two months later, the privacy office discovers it four months later, and by month six, three other departments have signed their own contracts with similar tools because no one knew there was a process. Now you have four overlapping vendors, four data flows nobody mapped, and a clinical staff that has been "trained" by four different vendor reps with four different scripts. That is not an AI problem. That is a governance vacuum, and the vacuum is what the CHAI playbooks are trying to fill.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Where I'd Actually Start, If This Were Landing On My Desk Monday<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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Eight playbooks at once is overwhelming, and I do not think CHAI intends for anyone to implement them all in parallel. So here is what I would actually suggest, given what I have seen so far across systems I have worked with:<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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1. Start With Third-Party Management And Responsible Data Management.<\/strong> These two are where the operational pain is highest right now, in my opinion, because every ambient AI, every clinical decision support tool, every revenue cycle automation is a third party touching protected data. If you only build two of the eight in the next quarter, build these. They will catch the most risk for the least political effort.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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2. Map Organizational Structure Before You Write Organizational Policy.<\/strong> I see systems try to write the policy first, and then realize halfway through that the policy assumes roles, committees, and escalation paths that do not actually exist yet. Figure out who owns what, then write the policy that codifies it. Not the other way around.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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3. Treat Education, Training and Feedback As A Year-One Investment, Not A Year-Three Cleanup.<\/strong> Clinicians using AI tools without context is the single fastest path to either underuse (the tool sits there) or overuse (the tool gets trusted in situations where it should not be). The training is not a nice-to-have. It is the difference between adoption and adoption theater.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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4. Use Risk And Impact Assessments To Pace Yourself.<\/strong> Not every AI use case carries the same risk. An ambient scribe for documentation is not the same risk profile as an algorithm influencing triage decisions. The playbook on risk and impact assessments is essentially permission to move faster on low-risk use cases and slower on high-risk ones, which is the right answer, and which a lot of governance committees struggle to give themselves permission to do.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The Quiet Win Here<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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What I think gets missed in coverage of releases like this one is that the bigger value is not the eight documents themselves. It is that a shared baseline lets health systems stop competing on governance and start collaborating. Your AI policy does not need to be a competitive differentiator, but your clinical outcomes do, your patient experience does, and your operational excellence does. Governance is the floor that lets the rest of the work stand up safely.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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The CMIO I mentioned at the start of this post emailed me yesterday asking what I thought of the CHAI release. I told her the same thing I would tell anyone reading this: you are not behind, the work in front of you just got more legible. The committee that has been re-debating the same five questions every month now has a starting framework that is not yours to invent. Use it as a baseline, adapt the 20% that is genuinely specific to your system, and spend the time you save on the work that actually moves outcomes for patients.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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That feels like a good week for healthcare AI governance, honestly.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Ready to put people first in your AI strategy?<\/a><\/h3>\t\t\t\t<\/div>\n\t\t
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The Governance Playbook Your Health System Was Probably Going to Write Anyway A CMIO I was talking to a few weeks back shared something with me that I keep thinking about. Her health system had stood up an AI governance committee about eighteen months ago. 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