New HLC–ZS Report Calls for Unified National Strategy to Advance AI in Healthcare

A new report released by the Healthcare Leadership Council (HLC) and consulting firm ZS outlines growing concerns over the fragmented regulatory landscape surrounding artificial intelligence in healthcare and offers a policy roadmap to accelerate safe, effective AI adoption across the sector.

Titled Unleashing AI’s Potential for Patients: A Cross-Sectoral Roadmap for Healthcare, the report is based on interviews with leaders from 27 HLC member organizations, representing a broad range of healthcare stakeholders. It identifies regulatory complexity, data infrastructure challenges, and end-user trust as the three main barriers preventing more widespread AI use in patient care.

“AI can further revolutionize patient care and reduce provider burden, but only if policymakers and industry move in lockstep,” said Maria Ghazal, President and CEO of HLC. “We need a clear, forward-looking national standard that harmonizes regulations and builds trust across all constituency groups, especially patients.”

Despite the growing promise of AI to improve diagnostics, enhance operational efficiency, and reduce costs, the report warns that inconsistent regulations at the state and federal levels, coupled with a lack of infrastructure and workforce readiness, are slowing progress. These challenges not only complicate implementation for healthcare organizations but also risk creating disparities in access and outcomes.

To address these issues, the report lays out nine policy recommendations grouped under three key themes:

Governance and Regulatory Complexity
The authors call for centralized federal legislation to replace today’s patchwork of policies. Modernized, harmonized regulations should clearly define accountability and offer liability protections for appropriate AI use in clinical care.

Data Access and Infrastructure
The report urges investment in infrastructure that supports data readiness and interoperability, along with clear standards for data transparency and bias mitigation. Universal definitions for AI use cases would also help create consistency across the industry.

Capabilities and End-User Trust
Recommendations include a focus on workforce development, with updated training programs and incentives to foster AI literacy among clinicians and healthcare staff. Building trust in AI tools through education and transparency is seen as essential for adoption at the clinical level.

The report also offers 25 optional tactics to support the nine recommendations, emphasizing flexibility and practicality. These suggestions are intended to serve as a resource for both industry leaders and policymakers looking to implement change without prescribing a one-size-fits-all approach.

“This report serves as a practical guide for how public and private stakeholders can work together to unlock AI’s full potential in healthcare,” said Bill Coyle, Chairperson of ZS. “Removing these barriers can improve care quality, strengthen the healthcare workforce, and advance more patient-centered care.”

Ghazal added that the uneven pace of AI policy at the state level underscores the urgency of federal leadership. “States like Utah are already acting, allowing AI to support prescription renewals, which shows real potential—but it also reveals how inconsistent policy development can create confusion and inequity,” she said. “A unified national strategy is needed to ensure that all patients benefit safely and equitably from AI innovation, no matter where they live.”

The full report is intended as a framework to help guide future legislation, regulation, and public-private collaboration.