Understanding Users’ Intention to Adopt AI Nutrition Chatbots: Insights from UTAUT2

Mao, L., Lu, P., & Mengqi (Maggie) Liao. “Understanding Users’ Intention to Adopt AI Nutrition Chatbots: Insights from UTAUT2,”paper to be presented at the 76th annual ICA conference, June 2026 in Cape Town, South Africa.  Abstract: The current poor nutrition issue among underserved and nutrition-sensitive groups in the U.S. underscores the structural inequities in nutrition uptake. This study investigates factors influencing the adoption of AI-powered nutrition chatbots, ChatDiet, through the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) framework. A national U.S. sample (N = 1,352) was collected through a survey. The study determined that performance expectancy, social influence, facilitating conditions, and hedonic motivation positively predicted the adoption intention of AI nutrition chatbots with significance, whereas effort expectancy exerted a negative effect. Privacy concerns and demographic factors were not significant. These findings extend UTAUT2 by illustrating how conversational AI technology may reduce technological barriers and enhance health information accessibility. It provides valuable insight for AI chatbot service providers and policymakers in understanding the adoption challenges and provides practical guidance for the successful implementation of the AI nutrition chatbot tool.