Can AI beat search engines for trip planning?

New study reveals how GenAI is reshaping the way we search for travel information, and when we still prefer to “just Google it”

Featured faculty: Lisa Wan
Written by Pan Jingyi

It was supposed to be a fun summer trip to Puerto Rico last year, as a Spanish couple had done everything ChatGPT planned, until they were refused to board the plane for not obtaining proper paperwork. In another case, two tourists were lost in a rural Peruvian town trying to find an imaginary destination suggested by AI.

AI has been hailed as the new technological evolution, but these stories remind us not to take technology at face value. On the other hand, these cases also highlight how trip planning has moved from a search bar of internet browsers to ChatGPT, DeepSeek, Grok, and the like. Scrolling through a sea of blue links is gradually replaced with a single prompt.

“Opting for an unfamiliar and novel search method like GenAI can be seen as a risky choice for making concrete plans.”

Professor Lisa Wan

“When ChatGPT was first introduced, we immediately sensed its strong potential for tourism information search, which largely depends on context and user preferences,” says Lisa Wan, Associate Professor of the School of Hotel and Tourism Management and the Department of Marketing at the Chinese University of Hong Kong (CUHK) Business School.

“Unlike traditional search engines that primarily provide fragmented information through hyperlinks, generative AI, or GenAI, can synthesise information, generate narratives, and adapt responses to users’ preferences.”

With much positive and negative news surrounding GenAI, Professor Wan seeks to understand what travellers actually perceive of the new technology. Working with Li Yuan of Zhejiang University, along with Luo Xiaoyan and Ding Xu of Sun Yat-Sen University, she conducted the research Advancing information search through GenAI: the roles of search type, travel motive and GenAI customisation level.

Across a series of studies involving more than 800 participants from different countries, the team examined when people lean towards GenAI or retreat to traditional search engines. They find that travellers’ willingness to use GenAI depends on their search purpose, travel motives, and whether the AI agent is tailored for trip planning.

When GenAI is less trustworthy

Trip planning often starts from curiosity and then turns into concrete actions. Individuals who come across a destination on social media or over casual conversation may want to find more about the must-sees, the overall vibe, and, as their interest deepens, may seek further information on specific prices and booking options.

Based on the above process, the researchers grouped these behaviours into two search types: non-decision-based, where individuals browse for general information about a destination, and decision-based, when more detailed information is sought for final decision-making.

“These differences can influence which search tools people choose,” Professor Wan says. “In the decision-based search, a small bad decision based on inaccurate information can turn into bigger problems, causing consumers to be more cautious.”

When participants are in decision-making mode, they prefer to gather information using traditional search engines. “Opting for an unfamiliar and novel search method like GenAI can be seen as a risky choice for making concrete plans,” she adds.

Professor Wan notes that new technologies often face a natural trust gap, especially when mistakes have significant consequences. Moreover, scepticism towards GenAI also reflects a rational assessment of its limitations in providing real-time and verified data, as reported in recent news.

In non-decision-based situations, however, the pattern shifts. When people are causally exploring or thinking about a destination, GenAI’s conversational style and ability to synthesise broad information become more appealing.

Traveller’s mindset and customisation make a difference

Looking further into what factors might encourage people to use AI in decision-making scenarios, Professor Wan and her collaborators found that the travel motive is the crucial piece. Specifically, participants motivated by a utilitarian goal that focuses on efficiency and convenience reported a higher preference for GenAI, whereas those with a hedonic motive of prioritising fun and pleasure are more likely to stick with traditional search engines like Google.

For utilitarian travellers, GenAI is preferred for its ability to filter information and organise search results, reducing the effort to compare options manually. Meanwhile, hedonic travellers enjoy the traditional browsing experience, mostly because search engines feature a richer mix of photos, videos, maps, reviews, and unexpected discoveries.

“Those prioritising fun and pleasure may find the variety and richness of multimedia content more appealing, providing a more immersive and enjoyable searching experience compared to the textual responses generated by GenAI,” says Professor Wan.

Customisation levels also affect user preference for AI. As booking platforms increasingly embed AI plugins for specific tasks, such as suggesting available hotels based on user preferences and providing customer service via AI chatbots, the study finds that such customisations can boost trust in GenAI.

How the tourism industry should adopt and develop GenAI

Given that GenAI is often more preferred in the non-decision stage, Professor Wan suggests platforms make an AI assistant visible in the main search bar to inform travellers general information about destinations, such as major attractions and cultural highlights. Another application is to display GenAI responses alongside traditional search results, allowing travellers to cross-check information easily.

While AI transformation continues to gain momentum, Professor Wan observes that fundamental challenges remain. “Many firms invest heavily in AI solutions but see limited results in daily operations. Two common obstacles are the lack of in-house talent to integrate AI into workflows and the tendency to adopt generic tools that don’t match real user demand.”

Furthermore, she observes that rapid AI advancements and shifting customer demand require firms to continually adapt this technology. “Rather than treating GenAI adoption as a one-off technological upgrade, firms need to view it as an organisation transformation process that involves gradual development, cross-functional collaboration and iterative experimentation.”

The future of travel planning

Professor Wan believes that AI will not completely replace search engines just yet, at least in the near future. Instead, travel information would be more distributed, with different tools serving different purposes. “GenAI is more likely to complement travel planning rather than substitute the traditional way,” she adds.

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Interestingly, she suggests that social media will be the close contender for search engines. In Chinese Mainland, for example, RedNote has already become a starting point for many travellers for its first-hand reviews. “The real shift is towards interactive, experience-rich and peer-validated information, something that social media and GenAI offer in different ways.”

Another takeaway is a concern about how GenAI can subtly change how travellers engage with places and experiences. Therefore, she encourages travellers to keep interacting with locals and communities. “The goal is not to reject intelligent tools, but to remain attentive to how they reshape human capabilities and experience.”