Generative Artificial Intelligence in Culinary Tourism Planning: An Exploratory Study on the Effects on Information Search and Travel Behaviour Among Generation Z

The rapid advancement of generative AI (artificial intelligence) is transforming digital environments and reshaping how travellers search for travel-related information. Despite the growing adoption of AI technologies within the tourism industry, limited academic research has examined how generative AI influences pre-trip information search and decision-making behaviour, particularly among Generation Z in the context of culinary tourism. This study investigates how Generation Z integrates generative AI into the pre-trip planning phase of culinary trips and how AI supports decision-making processes. A qualitative research design was applied using a digital diary approach consisting of pre- and post-interviews combined with a structured diary task. Ten purposively selected Generation Z participants documented their real-time interactions with generative AI tools during the planning of a culinary trip. The collected data were analysed in MAXQDA24 using a combined inductive–deductive coding approach. The findings reveal that generative AI primarily functions as an inspirational and efficiency-enhancing co-creation tool during early travel planning stages. Participants used AI to generate destination-specific food recommendations, identify local dishes, discover restaurants and structure culinary itineraries. AI-generated suggestions were typically verified using additional platforms before final decisions were made. The study contributes to a deeper understanding of how generative AI integrates into various stages of the pre-trip planning process and how it complements traditional information sources within the context of culinary tourism and gastronomic activities.