The Last Mile of AI Implementation
Health systems have mastered the AI pilot, but scaling is a different story. The metrics are clear: 70% of change efforts fail in hospitals and 95% of genAI pilots have yet to demonstrate meaningful ROI. Health system leaders face a flood of vendor demos and pressure to have an AI strategy, but lack the structured frameworks, guides, and standards to effectively make decisions and drive sustainable AI transformation.
That’s where The Playbook: Implementing AI in Healthcare comes in: a comprehensive set of maturity frameworks, role-driven roadmaps, and operational tools that guide health systems through the last mile of implementation. DiMe focuses on the “how,” building on the field’s growing consensus around responsible AI principles, including frameworks from partner organizations such as the Coalition for Health AI (CHAI), to create practical implementation pathways.
Multiple groups have published foundational guidance for responsible health AI. These include principles and frameworks like CHAI’s Responsible AI guide, the WHO’s ethics and governance guidance, NIST’s AI Risk Management Framework, ISO/IEC standards for AI system quality and safety, and professional society recommendations across medicine and informatics. Collectively, they define expectations for transparency, risk management, and accountability. These foundations are necessary, but these standards alone don’t solve the day-to-day challenges that determine whether an AI tool becomes a durable part of care delivery.
The Playbook addresses that gap by providing operational artifacts that embed directly into hospital governance, procurement, and clinical workflows. Where industry standards call for transparency through model cards, The Playbook shows health systems how to use those cards during procurement and local validation. Where responsible AI frameworks outline governance principles, The Playbook operationalizes it by integrating structured evaluation criteria and mandatory governance processes throughout the AI lifecycle, from planning to continuous monitoring.
Over the past year in partner convenings for The Playbook, it has become clear that the tools that fail at scale aren’t always the ones with technical flaws. The failures are the ones that can’t integrate into existing workflows and aren’t localized to the parameters of unique systems.
As Lucy Orr-Ewing, Chief of Staff and Head of Policy at CHAI, puts it: “CHAI applauds DiMe’s new Playbook on AI Implementation. This resource tackles the crucial ‘last mile’ of integration and gives the community the wherewithal to move from concept to impact in real-world care. We are delighted to work with DiMe and the ecosystem to build trust and accountability in health AI.”
The approach recognizes that standards and implementation must work in tandem. Standards without implementation become paperwork; implementation without standards risks harm. The Playbook ensures health AI is both trustworthy in theory and effective in practice.
Health AI is past the pilot phase. Building enterprise-scale deployments that are safe, equitable, and sustainable is the next challenge. Partnerships such as The Playbook: Implementing AI in Healthcare provide the operational infrastructure to bridge the gap between trustworthy AI and real-world practice, turning pilots into measurable patient impact.
