- The state of Utah is launching a pilot program that allows AI to automatically renew certain prescriptions for chronic diseases without physician involvement.
- The program is a partnership with the healthcare startup Doctronic, which began discreetly in December 2025.
- This marks the first time in the United States that AI has directly taken on a sensitive core medical task: prescribing medication.
- The goal is to reduce costs, limit medication disruptions, and improve access to care, especially in areas with doctor shortages.
- The AI will review prescription history, ask clinical questions similar to a doctor, and decide whether or not to renew.
- If any signs of risk are detected, the system automatically transfers the case to a human physician.
- The program is limited to 190 common medications; painkillers, ADHD medications, and injectables are all excluded.
- In data submitted to regulators, Doctronic stated that the AI matched doctors’ treatment decisions in 99.2% of 500 urgent care cases.
- The first 250 prescriptions for each drug group will be manually checked by doctors before the AI operates fully autonomously.
- Doctronic has purchased professional liability insurance for the AI, placing the system under the same level of legal liability as a physician.
- The current cost is $4 per renewal, expected to drop significantly as it scales, and may be covered by insurance.
- Medical associations warn of the risks of drug abuse, missed drug interactions, and subtle clinical signals.
- The FDA has not yet issued an official stance and may intervene if it determines this AI is a medical device.
- Utah views this as a policy experiment, accepting controlled risks to pave the way for medical AI innovation.
- Doctronic is negotiating expansions into other states such as Texas, Arizona, and Missouri.
📌 Conclusion: The U.S. state of Utah is making a big bet by granting AI the power to renew prescriptions, setting an unprecedented precedent in American healthcare. With a 99.2% accuracy rate according to corporate data, this model promises to reduce costs and improve access to care. However, the line between innovation and risk remains thin,especially as the FDA has yet to clearly define its regulatory role for AI “practicing medicine” in 2026.
