Perception-Adoption Gap of an AI Dietary Management App in Real-World Dining Settings: A Field Study

Background/Objectives: Although efficacious in randomized trials, the real-world adoption of AI-driven dietary management applications remains uncertain across diverse dining contexts and populations. Methods: This field-based observational study was conducted over 18 days at three real-world dining sites in Shanghai, China, enrolling 181 participants stratified into three groups based on food service style and customer attribute. A cross-sectional survey was administered on day 9, followed by a 9-day prospective usage tracking period. Results: After adjusting for sex, Group 2 (staff cafeteria with fixed-portion dishes) had the highest adjusted mean usability score at 71.20 (p < 0.001). Group 3 (community canteen) had the highest mean scores for information quality (16.57, p = 0.03) and perceptions of intended use in nutrition (12.01, p = 0.08). However, Group 3 recorded zero active usage sessions despite favorable initial perceptions. Conclusions: Favorable user perceptions of this AI-driven dietary management tool did not automatically translate into adoption. Scenario-specific usability and digital divide constraints define the boundary of real-world efficacy; moreover, AI may amplify existing dietary self-management behaviors rather than creating them de novo.