Overview
Artificial intelligence (AI) increasingly reaches into every aspect of daily life and is transforming our world in remarkable ways. Healthcare is one area of exceptional progress. HL7 International provides foundational leadership in the AI space. It convenes public and private experts worldwide to build understanding and consensus on the promises, complexities, and challenges at the crossroads of standards, interoperability, and AI. HL7 Fast Healthcare Interoperability Resources (FHIR®) and many other standards also provide the backbone and building blocks of emerging AI highways.
HL7 AI Initiatives: Strategic Focus Areas
As a standards development organization (SDO) with deep, broad-ranging international and United States (U.S.) stakeholder members, HL7 has a front-row seat to both the promises and perils emerging with AI use in healthcare. We are addressing these issues and breaking new ground in AI. HL7 is a rich resource with Leadership steeped in AI, including our CEO Professor Rachel Dunscombe and dedicated Chief AI Officer Dr. Daniel Vreeman, DPT. HL7 has an AI Office focused on establishing foundational standards for safe, trustworthy, and scalable AI in healthcare and convening the global community driving this transformation.
Four strategic pillars and distinct workstreams guide the HL7 AI Office in achieving transformative impact. These include:
Standards
Building the AI-ready interoperability stack for safe, explainable AI with provenance capabilities that advance human health.
Global Leadership & Partnerships
Convening the worldwide AI+health community to align standards, shape policy and accelerate responsible innovation.
AI Innovation Lab
Incubating AI solutions to enhance member experiences, accelerate standards development and pioneer new ways of working.
Community Excellence
Empowering implementers with tools and best practices for responsible, standards-powered AI deployment.
HL7 AI Webinar
As part of its AI work, HL7 hosted a recent webinar on the topic of Global AI in Healthcare: Policy, Patterns and Innovation Hotspots Worldwide. A full recording of this webinar can be accessed at: https://vimeo.com/1220030398/df74d73c85?share=copy.
Webinar speakers Daniel Vreeman, DPT, HL7’s Chief AI Officer; Rachel Dunscombe, HL7’s Chief Executive Officer; and Michael Lawley, PhD, Group Leader, Health Data Semantics and Interoperability at the Australian E-Health Research Centre, discussed many issues including:
- What role are HL7 and its AI Initiative playing?
- How can notable country and regional initiatives light the way?
- What key policy barriers and enablers exist in the healthcare AI space?
- Are there consensus frameworks that offer needed wisdom and best practice?
- What are special considerations for healthcare AI in LMIC settings?
HHS AI Agenda and “One HHS” Initiative
A key featured expert at this event and the Fall 2026 HL7 Working Group Meeting was Jesse Isaacman-Beck, PhD, Director of the Division of Artificial Intelligence Policy and Strategy, Office of the National Coordinator for Health IT (ONC), U.S. Department of Health and Human Services (HHS).
Dr. Isaacman-Beck outlined HHS’ AI Strategy and a “OneHHS” Approach that builds upon the July 2025 overarching America’s AI Action Plan [https://www.whitehouse.gov/wp-content/uploads/2025/07/Americas-AI-Action-Plan.pdf]. He explained, “HHS is supporting the sector to adopt AI safely, effectively, and at scale in clinical care. We are taking concrete actionswithin our statutory authorities – regulation, reimbursement, and research and development – with a use-case-by-use-case focus.” This involves:
- Uniting Divisions – FDA, CMS, NIH, CDC, ONC and others coordinating under a single AI strategy;
- Eliminating Silos – Information shared wherever appropriate with no friction or duplication; and
- AI Adoption at Scale – Coordinating action across the full HHS portfolio to drive real-world implementation.
Isaacman-Beck also outlined steps HHS is taking in response to key themes expressed by responders to the February 2026 HHS Health Sector AI RFI, which asked, “How can HHS use regulation, reimbursement, and research and discovery to accelerate the use of AI in clinical care?
These HHS efforts are:
- Regulation: Harmonizing and Clarifying Rules – Coordinating across agencies to clarify which rules apply to which AI use cases — oversight proportionate to risk, eliminating fragmentation that slows adoption.
- Reimbursement: Paying for Value and Outcomes – Modernizing reimbursement models to reward AI-enabled efficiency and measurable patient outcomes — not just tool adoption and use.
- Research and Development: Defining Evidence to Ensure Efficacy and Accountability – Building the evidentiary foundation through real-world pilots, shared datasets, and validated workflows — with clear accountability for AI outputs.
- Driving Data Liquidity for Scalable Outcomes – AI-ready data, interoperable standards, and shared infrastructure are prerequisites for effective regulation, reimbursement, and research and discovery.
HL7 AI Initiatives: Policy Pillars
HL7 is responsive to calls for input on emerging healthcare issues such as AI in the global and U.S. policy environment. Examples of recent HL7 AI policy letters can be found at:
[HHS Health Sector AI RFI]
[Request for Information (RFI) on the Development of an Artificial Intelligence (AI) Action Plan]
A key HL7 AI policy recommendation is that governments should broadly adopt voluntary consensus healthcare standards in regulatory and sub-regulatory policies governing AI use. This includes standards for creating, deploying, operating, measuring, reporting, and ensuring the transparency, safety, and privacy needed for AI use. Adopting voluntary consensus standards that comply with the World Trade Organization’s Agreement on Technical Barriers to Trade, such as American National Standards Institute (ANSI)-accredited American National Standards, is the optimal way for regulation to support the competitiveness of United States innovation in AI. HL7 also notes that AI transparency is paramount because clinical care operates in a high-stakes, regulated, trust-dependent environment where opaque decision-making can directly affect patient safety, equity, and legal accountability.
Conclusion
Moving forward, we are planning more AI-focused HL7 policy discussions and HL7 AI Global Passport Series webinars in 2027. We look forward to engaging you and hearing the expertise of our HL7 members and the broader public and private-sector community!
