Purpose: We are in a time of rapid adoption of artificial intelligence (AI) in medical care and medical education. We sought to determine the patterns of use and training in AI among family medicine (FM) residents.Methods: The 2025 American Board of Family Medicine (ABFM) National Resident Survey (NRS) was administered in October 2025 to all FM residents who completed the In-Training Exam. Residents were asked about their use of AI in the last month and any education about AI use they received in the last 6 months. Resident demographics were obtained from ABFM administrative databases.Results: A total of 15,259 residents completed the AI questions (response rate: 99.6%) with 10,858 residents (71.1%) reporting they used AI in the last month. The most common uses reported were for medical reference (40.7%), clinical decision support (31.9%), learning outside of patient care (23.6%), and ambient documentation of clinical encounters (21.9%). Only 36% reported any AI education or training in the last 6 months.Conclusions: Most FM residents reported recent use of AI tools, reflecting integration of these technologies into routine educational and clinical activities. However, formal training on AI use appears limited, suggesting a gap between adoption and structured competency development. The widespread use of AI by family medicine trainees has risks and opportunities for our future primary care workforce that will require new critical appraisal skills and new methods for teaching and assessing clinical reasoning.
