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Tourism destination stereotypes and generative artificial intelligence (GenAI) generated images

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  • Jingjie Zhu
  • Lingxue Zhan
  • Jie Tan
  • Mingming Cheng

Abstract

Generative artificial intelligence (GenAI) has started transforming the tourism industry with wide research implications. While recognising its transformative power, tourism literature failed to identify the dark side of GenAI. Using advanced image analytics across 10 tourism destinations, this research investigates how GenAI-generated images reinforce tourism destination stereotypes. Our findings reveal that GenAI tends to generate highly homogenised images, which cannot fully capture the diversity of destinations, leading to stereotypes. This study advances extant tourism literature by providing critical insights into the complex relationships between generative artificial intelligence and tourism.

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  • Jingjie Zhu & Lingxue Zhan & Jie Tan & Mingming Cheng, 2025. "Tourism destination stereotypes and generative artificial intelligence (GenAI) generated images," Current Issues in Tourism, Taylor & Francis Journals, vol. 28(17), pages 2721-2725, September.
    • Handle: RePEc:taf:rcitxx:v:28:y:2025:i:17:p:2721-2725
    DOI: 10.1080/13683500.2024.2381250
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