The Convergence Gap in AI Life Sciences Regulation
Regulators describe AI, digital health, and clinical trial law as converging, but FDA, UK, and Chinese actions show the frameworks are still moving on separate, misaligned tracks.
Regulators describe AI, digital health, and clinical trial law as converging, but FDA, UK, and Chinese actions show the frameworks are still moving on separate, misaligned tracks.
Divergence in AI rules across the US, EU, and China is driven less by geography than by conflicting definitions of what counts as a regulated AI function.
FDA's own framework gaps show interaction risk matters as much as accuracy, but the on-premise architecture fix now circulating is a contested proposal, not a settled control.
US data provenance, UK product classification, and Chinese jurisdictional scope are all cracking under AI health tools that don't fit pre-AI regulatory taxonomy.
Nature Medicine's new framework for evaluating generalist medical AI outpaces FDA's device-modification tools, leaving capability-tier governance to buyers.
Industrial AI systems now need functional safety, AI governance, and sector regulation layered together, and buyers should verify each layer separately.