Artificial intelligence in clinical practice: Usage trends and educational implications across the medical hierarchy

Artificial intelligence (AI) is increasingly integrated into healthcare, offering opportunities to enhance clinical decision-making, efficiency, and patient outcomes.Despite rapid adoption, variability in AI use, confidence, and formal education acrosslevels of medical training and specialties remains poorly understood.

To evaluate patterns of AI usage, confidence, educational exposure, and perceptions of AI training across the medical hierarchy, with particular attention to differences between gastroenterology (GI) and internal medicine (IM) providers.

A descriptive, cross-sectional survey was conducted at an academic tertiary care medical center. A 25-item REDCap-based questionnaire assessed AI use, frequency, confidence, formal education, regulatory awareness, and attitudes toward AI curriculum integration among medical students, residents, fellows, and attending physicians. Descriptive statistics and chi-square tests were used for analysis, with significance defined as p < 0.05.

Among 120 respondents, 83.5% reported AI use in clinical or educational activities, with 42.6% indicating daily use. Residents (92.3%) and medical students (87.8%) reported significantly higher AI use compared with attending physicians (61.5%). Overall, 73.7% of GI providers used AI; however, 47.3% reported low confidence, and none reported formal AI education. In contrast, 25% of IM providers had received structured AI training, and 56.1% were aware of HIPAA-compliant AI tools, compared with 15.8% of GI providers. All GI respondents (100%) supported the incorporation of formal AI education into medical curricula.

AI use is widespread across medical training levels, yet formal education, confidence, and regulatory awareness lag behind adoption, particularly among subspecialty providers such as gastroenterologists. These findings underscore the need for structured, specialty-specific AI education integrated throughout medical training to ensure safe, effective, and equitable use of AI in clinical practice.