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Why travelers prefer humans over artificial intelligence (AI): Developing and testing an AI aversion model in tourism
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DOI：10.1016/j.tourman.2026.105494.png)
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Abstract
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As tourism businesses increasingly adopt artificial intelligence (AI) to enhance traveler decision-making, a persistent reluctance to rely on AI-generated recommendations has emerged as a critical barrier. This research addresses this gap by developing and validating an AI aversion model that identifies the factors driving traveler resistance to AI-generated recommendations. Using a mixed-methods approach, this research uncovered five core drivers rooted in the perceived absence of human nature attributes: lived experience, emotional engagement, contextual understanding, domain specific knowledge, and proactive engagement in communication. Twenty-three items were developed and validated in a multicultural context. Additionally, we revealed that individual differences (i.e., rational vs. emotional personalities) play a moderating role, which can offer a way to mitigate the negative impacts of AI. The findings offer theoretical contributions by enriching the understanding of AI aversion and repositioning technology resistance through a human lens and extending practical implications for firms aiming to integrate AI effectively.
Keywords:
Artificial intelligence (AI)
AI aversion
Technology resistance
Human–AI interaction
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