As federal AI policy takes shape, it’s clear that healthcare innovation is entering a new era — one that demands both technical progress and public trust.
The White House’s latest AI Action Plan pushes for national standards, clinical validation, and regulatory sandboxes to accelerate the safe, responsible use of AI in healthcare. It also warns that tools deployed without transparency, oversight, or clinical grounding may face new scrutiny — especially as states begin passing their own health AI laws.
What is in the policy changes?
The White House recently unveiled its “AI Action Plan,” which includes plans to tie federal AI funding access to a state’s regulatory position, potentially negatively impacting states that impose what the administration deems “burdensome” AI regulations.
Another thrust of the plan is to establish regulatory sandboxes (AI Centers of Excellence), backed by NIST*-led health AI standards. These initiatives are framed around speeding up AI innovation—especially in healthcare and drug discovery.
* National Institute of Standards and Technology
Why does this matter for AI-powered Clinical Support Tools (CST) in Oncology?
- Regulatory tension: Many states (e.g., California, Colorado, Illinois, Maryland, Tennessee) are already passing health‑AI regulations—mandating transparency, clinician oversight, data provenance, and non‑ A federal approach that indirectly penalizes states with these laws could affect where and how AI-powered oncology tools can be deployed.
- Innovation sandbox opportunities: If regulatory sandboxes become available for healthcare AI, AI-powered tools could pilot cutting‑edge workflows in controlled environments — working hand‑in‑hand with researchers and regulators to validate real‑world evidence tools.
- Standardization leverage: With NIST and other agencies focused on health‑AI standards, we have a chance to help shape best practices — particularly around transparency, reliability, and clinical safety.
- Federal funding alignment: An ideal CST should minimize complexity for oncologists, while ensuring the ethical use of data aligns with the “innovation with accountability” narrative in the White House plan.
What should providers of AI-powered medical tools do?
- Monitor state-federal dynamics carefully to evaluate where their specific solution can launch and scale responsibly.
- Engage with regulatory sandboxes and align with emerging health-AI standards where possible.
- Maintain clinician trust as our north star, balancing speed with rigor, transparency, and real-world validation.
AI in healthcare is not just a tech problem — it’s a policy, workflow, and trust challenge. This legislation underscores how critical it is to be proactive at the intersection of innovation, transparency, and ethical design.
I would love to hear from other founders or clinicians navigating this space—how are you approaching regulation and federal‑state interplay?
Anna Forsythe is the Founder and President of Oncoscope-AI, the first platform to bring together real-time oncology treatment data, clinical guidelines, research publications, and regulatory approvals — all in one place, just like Expedia for cancer care. Available free to oncology professionals worldwide, Oncoscope-AI is redefining how cancer care information is accessed and applied.
A clinically trained Doctor of Pharmacy (PharmD), Anna also holds a Master’s in Health Economics and Policy from the University of Birmingham (UK) and an MBA from Columbia University. She previously co-founded Purple Squirrel Economics (acquired by Cytel in 2020) and led Global Value and Access at Eisai Pharmaceuticals, following earlier roles at Novartis and Bayer in clinical research and health economics.
