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The Clinical AI
Governance Playbook

A physician's framework for governing AI before AI governs you.

85% of health systems
increasing AI budgets

$0 budgeted for
governance frameworks

100% of shadow AI users
bypassed your IT policy

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The Problem

Your organization is governing AI the way it governed EHR rollouts. That's the problem.

Your staff is using ChatGPT to write clinical notes. Your residents are running differential diagnoses through consumer AI tools. Your administrators are feeding patient scheduling data into Copilot. None of it went through IT. None of it was reviewed by compliance. None of it is documented anywhere.

This is shadow AI. It is already inside your organization. And it is multiplying faster than your governance structure can absorb it.

"Shadow AI isn't a technology problem. It's a governance gap. The same gap that caused your last three digital health pilots to stall at scale."

Health systems are spending $50,000 to $150,000 with outside consultants to build governance frameworks from scratch, frameworks that address the technology but miss the clinical floor, frameworks built by people who have never held a license, never been responsible for a patient outcome, and never navigated what actually happens when policy meets physician behavior.

There is a better approach. It starts with a physician's perspective on what governance actually needs to do.

The Framework

Five elements of a governance structure that
actually holds at the clinical level.

The Clinical AI Governance Playbook introduces a five-element framework built from direct clinical experience, health system consulting engagements, and 40+ organizational assessments. Each element addresses a specific failure mode that generic IT governance frameworks miss entirely.

Clinical Risk Stratification

Not all AI carries the same risk. A scheduling tool and a diagnostic support algorithm are not the same governance problem. This element gives you a repeatable method to stratify risk by clinical proximity, consequence severity, and reversibility.

Shadow AI Detection and Amnesty

You can't govern what you can't see. This element provides a structured method to surface shadow AI use within your organization, map it to risk categories, and create an amnesty pathway that incentivizes disclosure without punishing the behavior that got you here.

Physician Integration Protocol

Governance fails at the clinical floor when physicians weren't in the room when the policy was written. This element structures the physician integration process so that clinical leadership isn't signing off on a document they had no hand in building.

Accountability Architecture

Someone has to own this. The accountability architecture defines roles, escalation paths, and decision rights so that when something goes wrong (and it will), your organization knows exactly who answers for it and what the response protocol is.

Living Governance: The Quarterly Review Cycle

A governance document that isn't updated is a liability, not an asset. This element provides a structured quarterly review cycle that keeps your governance framework current as AI capabilities, vendor relationships, and regulatory guidance evolve.

Who This Is For

This playbook was written for the person holding the organizational consequence.

Not for the vendor selling AI tools. Not for the consultant who will leave after the engagement ends. For the health system leader who will still be there when something goes wrong, and who needs a framework that works in the real operational environment, not in a conference room.

Chief Medical Officers navigating AI adoption pressure from the board and resistance from the medical staff simultaneously
Chief Digital Officers building governance before the legal department finds out what's already deployed
Chief Information Officers who need clinical alignment on policies that will actually be followed
VP of Quality and Patient Safety leaders who understand that AI errors in clinical settings are a different category of risk
Healthcare executives at PE-backed health systems where AI adoption velocity is outpacing governance infrastructure
Medical Directors and department heads who have been asked to "review the AI policy" and have no framework for what that means clinically

What's Inside

A complete governance architecture.
Not a starting point. A deliverable.

01

The Governance Gap Diagnostic

A 15-question organizational self-assessment that maps your current governance maturity, identifies the highest-risk gaps, and prioritizes your first 90 days of action. Most organizations score lower than they expect. That is useful information.
02

Clinical Risk Stratification Framework

The decision tree and scoring rubric for classifying every AI tool in your organization, from ambient documentation to clinical decision support to administrative automation. Includes worked examples from real health system deployments.
03

Shadow AI Inventory Protocol

A structured 30-day process for mapping what is actually in use across your organization. Includes the amnesty communication template, department liaison guide, and the IT inventory integration checklist.
04

The Physician Integration Playbook

How to build physician governance participation that is substantive, not performative. Includes the medical staff communication framework, the clinical champion identification process, and the structured review protocol for clinical-facing AI tools.
05

Accountability Architecture Template

Role definitions, RACI matrix, escalation protocol, and incident response framework. Ready to adapt to your organizational structure. Includes the vendor accountability addendum for third-party AI tools.
06

The Quarterly Governance Review Cycle

A repeatable process for keeping governance current. Includes the agenda template, the regulatory update integration protocol, and the AI portfolio review scorecard. One structured meeting per quarter. No standing committees required.
APP

Appendix: Templates, Policies, and Reference Library

Editable AI use policy template. Vendor assessment questionnaire. Shadow AI amnesty communication. Clinical champion nomination form. Regulatory reference guide (HIPAA, FDA, CMS, state-level). Everything you need to go from playbook to governance document without starting from scratch.

Why Dr. Sarah Matt

This framework was built by someone who has to live with the consequences.

Most AI governance frameworks are written by consultants who have never held a clinical license, never been responsible for a patient outcome, and will be gone before the policy is tested by a real incident. This playbook was written by a physician who has spent the last decade at the intersection of clinical operations and digital health strategy, watching governance fail and studying why.

Clinical Foundation

Practicing physician with an active license. The governance framework reflects how clinical decisions are actually made, not how an IT architecture document assumes they are made.

Operational Track Record

40+ health system engagements. Has watched the same governance failures repeat across organizations of every size, geography, and ownership structure. Pattern recognition, not theory.

Strategic Credibility

MD, MBA. National best-selling author of The Borderless Healthcare Revolution. Professor. Speaker. The framework holds up at the board level and on the clinical floor.

No Vendor Alignment

This framework is tool-agnostic. It does not favor any AI vendor, platform, or category. The only agenda is building governance that works for the organization using it.

Early Access

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The Clinical AI Governance Playbook