Exploring the Application of AI-Generated Image Technology in the Design of Agricultural Product Mascots for Tourist Destinations

This study aims to leverage current AI image generation technology to evaluate the potential of human-machine collaboration in mascot symbol design and explore potential strategies to address the crisis of homogenization in visual design. Based on a theoretical framework of semiotics and destination branding, this study combines cultural coding, AI prompt engineering, and expert calibration to transform local agricultural specialty products (ASP) into a mascot visual system. The MidJourney platform, which is relatively easy to use, was selected as the primary AI generation tool for this project. Following necessary manual optimization, three industrial design experts evaluated the generated AI visual codes via a structured questionnaire to measure their acceptability across five design dimensions. The results indicated that AI-assisted generation could rapidly produce diverse mascot concepts that embody distinct regional characteristics, though only a few met expectations. This may be attributed to the author’s limited proficiency in crafting prompts for this platform; performance was expected to improve significantly with further training. The experts’ evaluation of the AI-generated mascot designs revealed that overall acceptance was satisfactory, though the male protagonist scored slightly higher in terms of visual appeal and functional suitability. In conclusion, the authors argued that AI-generated image technology, when embedded within a human-machine cooperation loop, offers an effective and viable mechanism for mascot symbol design of agriculture-specific products in travel destinations.