PURPOSE
This study evaluated the knowledge, perceptions, and readiness of
preclinical osteopathic medical students and faculty to adopt artificial
intelligence (AI) tools in medical education, with a focus on perceived
benefits, concerns, and training needs.
METHODS
Following IRB approval, a 22-item cross-sectional survey was distributed
via Qualtrics to all preclinical students (n=292) and faculty (n=52) at
Burrell College of Osteopathic Medicine between May and July 2025. The survey
assessed formal AI training, perceived advantages, concerns, and preparedness
using Likert scales, multiple-choice, and free-text responses. Quantitative
data were analyzed descriptively in Excel; qualitative responses underwent
thematic coding.
RESULTS
Completed responses were received from 54 students (12%) and 15 faculty
(28.8%). Most respondents (85.2%) lacked formal AI training. Students
reported moderate baseline AI knowledge (mean = 3.07 ± 0.77) and identified
benefits such as enhanced knowledge acquisition, faster information
retrieval, and improved practice question generation. However, concerns
included overreliance, ethical risks, accuracy, privacy (27%), and job
displacement (16%). Most respondents emphasized the need for institutional
policies before AI integration.
Among faculty (66.7% male), 86.6% reported partial or substantial AI
knowledge, though 60% lacked formal training. Faculty primarily used AI for
generating practice questions (60%) and case vignettes (66.7%). Both groups
expressed caution regarding AI’s accuracy and ethical implications, aligning
with prior literature.
CONCLUSION
Despite limited formal training, both students and faculty recognize AI’s
potential to enhance educational efficiency. Concerns about accuracy, ethics,
and institutional readiness underscore the need for structured AI literacy
programs and policy development. These findings support proactive curriculum
planning to ensure responsible and effective AI integration in osteopathic
medical education.