HEAL-AI Act (H.R. 6077): What Educators, Health Systems, and HR Leaders Need to Know
H.R. 6077-Healthcare Education in AI Literacy Act-was received on 2025-11-18 and currently has 2 cosponsors. The bill amends the Public Health Service Act to fund AI education for medical students, residents, and faculty. If you run curriculum, workforce development, or training in healthcare, this is worth planning for now.
Quick Snapshot
- Grant size: Up to $100,000 per institution
- Admin cap: No more than 10% for administrative costs
- Priority: Institutions serving medically underserved communities
- Funding window: $1,000,000 per fiscal year, 2026-2030
- Status: Received 2025-11-18; 2 cosponsors
What the Grants Cover
- Education for medical students and residents on AI concepts, applications, and limitations
- Faculty development to integrate AI into teaching and clinical workflows
- Training on AI use in diagnostics, treatment recommendations, and clinical decision support
- Ethics, safety, bias, oversight, privacy, and informed consent related to AI in care
- Demonstrations that show practical use cases in real or simulated clinical settings
Grantees must make educational materials publicly available online and file annual reports on goals, spending, curriculum integration, and enrollment/completion data.
Who's Eligible
- Accredited medical or osteopathic schools and residency-sponsoring institutions
- Applicants that show the need for AI literacy in their curriculum and a clear implementation plan
- Institutions serving medically underserved communities receive priority consideration
Collaboration is encouraged with academic partners, nonprofits, and other entities. The bill also asks for fair geographic distribution across urban, suburban, and rural areas.
Practical Steps to Get Grant-Ready
- Form a steering group: Education leader, CMIO/CNIO, GME, compliance, HR, and IT.
- Run a quick audit: Where does AI already appear in the curriculum? What gaps exist?
- Pick 3-5 clinical use cases: Examples: imaging triage, documentation support, risk prediction, patient outreach.
- Define competencies: Safety, bias mitigation, oversight, data literacy, and patient communication.
- Line up partners: Nonprofits, simulation centers, or academic collaborators to strengthen the application.
- Plan for underserved impact: How the program benefits medically underserved communities.
- Decide on publishing: Where you'll post syllabi, slides, and course materials publicly.
Sample Budget (for a $100,000 grant)
- 60%: Curriculum development and faculty release time
- 20%: Tools, licenses, and simulation resources
- 10%: Training workshops and evaluation
- 10%: Administrative costs (meets the cap)
Reporting and Compliance Checklist
- Annual report with progress against educational goals
- Detailed accounting of how funds were spent
- Proof of curriculum integration and where AI content lives
- Enrollment, completion, and assessment data for funded courses
- Public links to educational materials produced with the grant
Suggested Metrics That Map to the Bill
- Number of students, residents, and faculty trained
- Competency attainment rates and assessment results
- Count of AI-integrated courses, clerkships, and simulations
- Use-case adoption in clinical or simulated settings
- Impact measures for medically underserved populations
Definitions (Plain Language)
- Artificial Intelligence (AI): Systems that make predictions or decisions influencing medical environments.
- Education and Training: Competency-based medical education that improves patient care through AI-aware practice.
- Qualified Medical Schools: Accredited institutions for medical or osteopathic education.
Renewals and Partnerships
Institutions may apply to renew grants to extend their AI education initiatives. Consider formal MOUs with academic or nonprofit partners to strengthen curriculum design, evaluation, and access to real-world case studies.
Implications for HR, Deans, and Program Directors
- Hiring and upskilling: Update job descriptions and CME plans for AI literacy and oversight competencies.
- Policy alignment: Align with institutional AI governance, data privacy, and model oversight policies.
- Faculty incentives: Offer protected time and recognition for curriculum leadership and evaluation work.
- Credentialing: Tie competencies to promotion criteria and continuing certification where possible.
Industry Collaboration Notes
Companies working at the intersection of healthcare and AI-such as MDGL (genomics and AI), CYRX (digital health), and AMGN (biotech)-may collaborate with institutions on educational demos, datasets, or supervised pilots. This section is informational and not investment advice.
Related Context on Underserved Priority
Because the bill prioritizes medically underserved communities, it helps to align proposals with federal designations and local needs assessments.
Optional Resources for Building AI Curriculum
Primary Sponsor and Recent Proposals
Representative Nanette Diaz Barragán has recently proposed:
- H.R.6077: HEAL-AI Act
- H.R.5840: Feed the Community Act
- H.R.5692: Marine Energy Technologies Acceleration Act
- H.R.5673: Stop the Trump Electricity Price Hikes Act
- H.R.3136: Protect our Public Health Workforce Act
- H.R.1901: CHIPP Act
Additional Notes on Disclosures
Quiver Quantitative estimates Representative Nanette Diaz Barragán's net worth at $3.5M as of November 27, 2025 (202nd highest in Congress by their live estimates). They report approximately $127.6K in tracked publicly traded assets and up to $110.0K in trades parsed from STOCK Act filings. You can track bills and financial disclosures on Quiver Quantitative's politician page for Barragán.
This article is not financial advice. See Quiver Quantitative's disclaimers for more information.
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