AI-Driven Visual Communication Strategies for Enhancing Engagement in Smart Hospitality Platforms

Abstract

The rapid evolution of Smart Hospitality has reshaped how tourists interact with service providers. Visual communication plays a pivotal role in influencing engagement, yet most digital content remains generic, limiting brand resonance. This study investigates AI-driven visual communication strategies to enhance engagement by bridging computer science and design communication. A mixed-method approach was employed, starting with the analysis of 120 hospitality visuals using K-means clustering and sentiment analysis to identify aesthetic patterns. Two stimuli sets were developed: Set A (Generic) and Set B (AI-Personalized with 70% preference similarity). A survey experiment (n = 156) involving Generation Y and Z users was conducted. Quantitative analysis revealed that AI-personalized visuals significantly outperformed generic content, with engagement scores increasing from M = 3.42 to M = 4.15 and trust levels rising by 21% (p<0.001). Qualitative feedback from NVivo thematic coding confirmed that users perceived AI-tailored visuals as more authentic and relevant. This study offers an interdisciplinary novelty by integrating computational machine learning with visual storytelling. The findings demonstrate how AI personalization within the IoT-linked Smart Hospitality ecosystem can bridge technical innovation with user-centered design to advance digital tourist experiences.