Inside the White House AI Action Plan: What Healthcare Leaders Think About America's Push for AI Adoption

Federal AI Action Plan Targets Healthcare Innovation and Adoption

In August 2025, the U.S. government unveiled a new federal AI Action Plan, titled "Winning the Race." This 28-page executive order addresses the slow adoption of artificial intelligence across critical sectors, including healthcare. Key barriers cited are distrust in the technology, complex regulations, and unclear governance and risk standards.

Key Steps to Foster AI Development and Deployment

The plan proposes several strategic initiatives to encourage a more experimental and open AI environment nationwide:

• Regulatory Sandboxes and AI Centers of Excellence: These hubs will allow researchers, startups, and established companies to test AI tools rapidly, with a commitment to sharing data and outcomes. Agencies like the FDA and SEC will support these efforts, alongside NIST’s AI evaluation activities.
• Domain-Specific Collaborations: Led by NIST at the Department of Commerce, these initiatives will bring together diverse stakeholders from healthcare, energy, agriculture, and more to develop national AI standards and quantify productivity gains from AI applications.
• National Security Assessments: The Department of Defense and Office of the Director of National Intelligence will regularly update assessments on AI adoption levels by the U.S. and global competitors, adjusting defense and intelligence strategies accordingly.
• Intelligence Sharing on Foreign AI Projects: Collaboration among intelligence agencies and departments like Energy and Commerce aims to monitor and address AI projects abroad that could impact national security.

One notable policy is the promotion of AI testbeds—secure, real-world environments where AI systems can be prototyped and moved toward market readiness. These testbeds will support a wide range of sectors, including healthcare, agriculture, and transportation.

Healthcare Industry Leaders React

Executives across the healthcare technology sector have shared mixed but insightful perspectives on the federal plan's impact.

Kent Dicks, CEO of Life365, praises the plan for providing "clarity innovators have been waiting for." He highlights how streamlined infrastructure approvals and clear standards can help scale AI tools that predict risks and keep patients healthier at home. According to Dicks, this roadmap positions the U.S. to lead in clinically driven healthcare AI that can be exported globally.

Dr. Jay Anders, chief medical officer at Medicomp Systems, expresses some skepticism. He points out that building infrastructure alone won’t ensure AI transparency or reliability, especially for predictive large language models. Anders calls for a stronger focus on how healthcare AI is trained, monitored, and constrained to prevent erroneous outputs.

Daniel Blumenthal, VP of strategy at MDClone, emphasizes the importance of large, high-quality, privacy-protected patient datasets. He advocates for synthetic data as a key enabler for responsible innovation in healthcare AI, allowing new insights without compromising privacy.

Patty Hayward, general manager of healthcare and life sciences at Talkdesk, sees the plan as a way to accelerate AI adoption during a time of financial pressure on hospitals and health systems. She stresses the potential of agentic AI to reduce administrative waste, lower costs, and expand access to proactive patient care.

Robin Roberts, director of health IT regulatory affairs at PointClickCare, notes the executive order signals a shift toward prioritizing meaningful technological progress. Roberts underscores that improving patient outcomes and reducing burdens on providers depends on adopting sound AI solutions, with careful attention to safety and privacy.

Abhi Gupta, CEO of Fold Health, describes the plan as a pivotal moment for AI as a national strategic priority. He highlights how infrastructure investments will support health systems implementing large language models for clinical documentation and population health analytics. Gupta also points to deregulation and open-source model development as drivers that will create opportunities for U.S. health tech companies to scale globally.

Conclusion

The new federal AI Action Plan sets a clear direction to accelerate AI adoption across healthcare and other sectors. While opinions vary on specifics, the consensus among industry leaders is that it provides a framework for safer, scalable, and more transparent AI innovation. Executives should watch for emerging standards, regulatory updates, and opportunities to engage with AI testbeds and partnerships.

For healthcare leaders aiming to deepen their AI knowledge and explore practical applications, resources like Complete AI Training’s latest AI courses offer valuable guidance on integrating AI tools strategically within organizations.