We’ve all heard the promises of AI in healthcare - but turning hype into real impact requires more than ambition. At nymble, we believe the key is control and trust. Healthcare isn’t a sandbox, and organizations can’t afford casual experimentation. That’s why our platform gives enterprise partners choice: whether to fully leverage generative AI, use it selectively, or not at all. By putting stakeholders in control, we reduce barriers to adoption and provide a safe, flexible p

This second part explores how existing laws — from medical malpractice to product liability — are being applied to AI in healthcare. The challenge is adapting these rules to AI’s complexity and evolving standards of care. With strong safeguards, due diligence, and a focus on patient safety, organizations can responsibly harness AI’s potential while managing the risks.

As AI tools like ChatGPT and ambient scribes become embedded in healthcare, a pressing question emerges: who is responsible when things go wrong? This two-part series explores the evolving landscape of AI liability. In part one, we examine why inaction carries its own risks, how AI is already embedded in care, and the key safety and data protection concerns. Part two will dive into the legal side of the blame game: the types of liability claims healthcare organizations may fa