Abstract
BACKGROUND: Previous AI literacy studies have been limited to clinical students and professionals and included subjective reporting. This survey study explored the extent of AI knowledge in health information professionals with subjective and objective questions. The objective of the study was to inform the International Federation of Health Information Management Associations (IFHIMA) and national health information bodies about current AI literacy levels and the education needs of their members. METHODS: A descriptive survey was adapted from two validated, previously-published study instruments. Survey data were collected between December 5, 2024, and February 28, 2025 using a self-administered Qualtrics (Seattle, WA) online survey link distributed by email to IFHIMA members. The survey link was also distributed on the LinkedIn professional networking platform (LinkedIn Corp; Sunnyvale, CA) by multiple IFHIMA members. Results were analyzed using Chi-square, ANOVA, and Tukey HSD post-hoc tests to assess the associations between the categorical response variables and the subjective survey question measures. RESULTS: A total of 176 participants began the survey. Data were cleaned to exclude 48 incomplete responses, leaving 128 complete and valid responses for analysis. AI knowledge varied by demographics; country of employment or residence and professional association membership were shown to influence familiarity with AI. Many health information professionals reported limited or no AI experience, and those with practical AI experience performed better on foundational AI knowledge questions, suggesting that experiential learning scaffolds AI literacy. Most respondents understood emerging AI-related threats. However, regardless of experiences with everyday AI tools, they struggled with AI modeling and product development. CONCLUSIONS: The study results identified a major gap in AI knowledge, and the authors provide input for educators aiming to align educational programs with job market demand by increasing AI knowledge content, addressing gaps through targeted curriculum development and educator training.