AI-Enabled Multilingual E-Menu Systems for Smart Restaurant Ordering: Examining Trust, Efficiency, and Customer Satisfaction

In the hospitality sector, AI has rapidly transformed service delivery and is particularly prevalent in restaurants where digital ordering systems are becoming more popular. The attention is on human-AI interaction in Jakarta's hospitality industry’s multilingual restaurant ordering systems with AI technology. The study investigates the correlation between AI interaction quality, ease of use perception, trust in AI systems, service efficiency, customer satisfaction, and intention to use artificial intelligence. Survey data from 230 restaurant customers in Jakarta who had experience with AI-based digital ordering systems was utilized in a quantitative research design. These were analyzed using Partial Least Squares Structural Equation Modeling (PLS–SEM). Perceived AI interaction quality and ease of use are significant factors that contribute to a greater level of customer confidence in AI-enabled ordering systems. Trust is associated with improved perceived efficiency and higher customer satisfaction, while continued intention to use is strongly correlated with customer satisfied. These results demonstrate the importance of ensuring that AI-enabled hospitality technologies are dependable, user-friendly interfaces, and communicate effectively with customers. The literature on AI-assisted hospitality services is reinforced by the inclusion of empirical evidence from a restaurant environment in an emerging market. From a managerial perspective, the results suggest that hospitality professionals should prioritize user-friendly AI interfaces and accurate multilingual capabilities to enhance customer experience and encourage more frequent implementation of digital service innovations.