UC Davis Launches AI Training Pilot for Emergency Medicine Residents
Published: 18 Mar 2026
Author: Precedence Research
The Department of Emergency Medicine at UC Davis Health has launched a pilot program designed to train medical residents in the use of artificial intelligence tools during clinical practice. The initiative focuses on helping residents learn how to apply generative AI technology to assist with documentation and clinical note-taking while caring for patients in the emergency department.
The program builds on technology already adopted by faculty physicians in outpatient clinics. By introducing the system to residents during their training, the institution aims to prepare future physicians to use AI responsibly and effectively in fast-paced healthcare environments.
AI-Assisted Documentation in the Emergency Department
The pilot program teaches residents how to use AI-powered note-taking tools during patient encounters. These systems can capture conversations between clinicians and patients and generate structured medical notes that summarise key details from the visit.
Residents are trained not only to use the tool but also to review and verify the accuracy of AI-generated documentation before it becomes part of the patient’s medical record. This step ensures that clinicians maintain oversight and accountability for the information recorded in the health system.
The approach aims to reduce the time physicians spend on administrative tasks, allowing them to focus more attention on patient care. In high-volume emergency departments, documentation demands can consume a significant portion of a clinician’s shift, making AI assistance particularly valuable.
According to Towards Healthcare, the U.S. Emergency Department Market is projected to experience significant growth, with estimates suggesting the market size will increase from USD 229.25 billion in 2026 to approximately USD 388.96 billion by 2035, representing a compound annual growth rate (CAGR) of 6.05% from 2026 to 2035. This market expansion is driven by the rising number of emergency visits, increasing prevalence of chronic diseases, growing trauma cases, and the continuous need for rapid, high-quality acute care services across the U.S.
Training Physicians to Use AI Responsibly
Beyond learning how to operate the technology, residents participating in the pilot program are also trained to understand the limitations and risks associated with artificial intelligence in healthcare. The curriculum emphasises critical evaluation of AI outputs, patient privacy considerations, and the importance of maintaining clinical judgment.
By teaching residents how to analyse and correct AI-generated information, the program aims to ensure that the technology is used safely and ethically. Faculty members guide trainees through real-world scenarios where AI tools may support but not replace- clinical decision-making.
Preparing the Future Healthcare Workforce
The initiative reflects a broader shift in healthcare toward integrating digital technologies into clinical workflows. As artificial intelligence becomes increasingly common in hospitals and clinics, training programs are beginning to incorporate these tools into medical education.
Through this pilot program, UC Davis Health hopes to equip emergency medicine residents with the skills needed to navigate AI-enabled healthcare systems. By combining hands-on training with education about risks and responsibilities, the program seeks to ensure that future physicians can use AI technologies effectively while maintaining high standards of patient care.
A recent report by Towards Healthcare highlights that the U.S. Emergency Department Market is witnessing steady development as healthcare systems invest in advanced emergency care infrastructure, digital triage tools, and improved patient flow management. Emergency departments provide critical services such as trauma care, cardiac and stroke management, diagnostic imaging, laboratory testing, and urgent medical treatment, making them an essential component of the U.S. healthcare delivery system.