Artificial Intelligence in Hepatology Training

Artificial intelligence (AI) tools are increasingly integrated into hepatology clinical practice and training, such as ambient scribes and note drafting in clinic, chart summarization on consult services, and AI–enabled platforms that synthesize evidence for point-of-care questions. While these tools may accelerate access to knowledge, they also introduce important educational and professional risks: (1) Trainees may become overly reliant on AI and never fully acquire core clinical skills, (2) AI–generated recommendations may be accepted without appropriate verification or contextualization, and (3) evolving boundaries on AI usage in scholarly pursuits and research.  Presented as a partnership between the Clinical Informatics and Digital Health Special Interest Group and the Training and Workforce Committee, this program provides a hepatology-centered framework for responsible AI use across 3 domains: enhancing hepatology education quality; using AI to enhance self-directed learning and evidence appraisal; and establishing guardrails for scholarly use of AI to maintain academic integrity. The session concludes with an interactive panel discussion using common scenarios to translate principles into implementable teaching strategies and program policies.