AI for All? Applying Diffusion of Innovation Theory to Healthcare AI Acceptance Across Demographic Groups

Artificial intelligence (AI) is transforming health care, yet little is known about how attitudes towards AI differ across cultural groups. Guided by Diffusion of Innovation (DOI) Theory, this study investigates how relative advantage, complexity, compatibility, trialability and observability predict attitudes towards AI in health care among White (n = 6,787), Black (n = 1,260), Hispanic (n = 1,787), and Asian (n = 575) Americans using Pew Research Center’s Wave 119 of the American Trends Panel. Chi-square, ANOVA, Z tests and regression analyses identified significant group differences: Asian and Hispanic participants reported more favorable attitudes than Black and White respondents. Across all groups, being male, perceiving greater relative advantage and compatibility, and perceiving lower complexity consistently predicted more positive attitudes. Among White participants, all DOI attributes were significant predictors. However, trialability and observability exhibited unique predictions for Black, Hispanic, and Asian participants. Findings offer theoretical and practical implications for achieving equitable AI adoption.