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Artificial intelligence is turning travel planning into a new layer of digital competition. Image by Firmbee/Pixaba.
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AI in Tourism: The New Engine of Travel PlanningAI Agents Accelerate Tourism Planning, but Their Accuracy and Data Will Be Crucial for Businesses and DestinationsBy Estefanía Muriel for Ruta Pantera on 10/16/2026 7:52:13 AM |
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| Can an algorithm design a better trip than a person who knows the destination? The question is no longer hypothetical. Technology platforms are already integrating artificial intelligence into searches for flights, hotels, restaurants, and activities, transforming a request written in natural language into an itinerary with multiple variables. This change affects travelers, but also tourism companies that compete to appear within these new layers of digital recommendations.
Adoption is already on a large scale. A Booking.com study published in July 2016 found that 68% of Colombian travelers had used AI tools while planning or developing a trip. These uses included price comparison, local recommendations, and tour searches. AI is therefore beginning to influence business decisions that were previously made through search engines, agencies, reviews, and personal recommendations. The business opportunity is clear, but so is the problem: an automatically generated recommendation may seem accurate without necessarily being actionable. Recent research shows that planning systems still struggle to simultaneously respect budget, schedules, distances, availability, and preferences. The challenge for tourism is not only to produce attractive itineraries, but also to ensure that artificial intelligence connects the digital promise with physical reality (Qi et al., 2026). AI Turns Planning Into a New Market Tourism planning is shifting from fragmented searches to interfaces capable of synthesizing information. Google explains that its AI travel tools can combine data from Maps, flights, and hotels to build personalized itineraries, while its latest features aim to take that process from inspiration to booking. For hotels, tour operators, and destinations, this means that visibility may increasingly depend on how their products are interpreted by algorithmic systems. Personalization also relies on user data. Google notes that Gemini can use information from connected services, such as searches, photos, and bookings, to tailor recommendations to individual interests and restrictions. From a business perspective, this capability opens opportunities to reduce friction and improve conversion, but it also increases the importance of the quality, currency, and structure of the data describing hotels, experiences, schedules, and tourist services. The shift also alters the competition for attention. Instead of presenting travelers with dozens of results to compare, an AI interface can summarize options and present a few alternatives. This can favor businesses with verifiable information and clearly differentiated products, while increasing pressure on companies with incomplete digital presence. The issue is no longer simply being online, but being readable and trustworthy by systems that generate recommendations. The Risk of Creating a Destination That’s Too Perfect The appeal of these systems has a well-known technical limitation: generating convincing language is not the same as verifying that every element of the itinerary exists, is available, or physically fits. A 2024 academic paper titled "TRIP-PAL: Guaranteed Travel Planning by Combining Large Language Models and Automated Planners," by de la Rosa et al ., already warned that language models could produce inconsistent plans or violate constraints, which is why they proposed combining linguistic models with automated planners capable of checking conditions. |
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The most recent research confirms that this problem remains unresolved. TREK: A Travel Reasoning and Evaluation Kit for LLM Agents in Complex Trip Planning, developed by Qi et al. (2026), assesses the ability of AI agents to design complex trips and verifies that included flights, hotels, and attractions exist, are bookable, fit the budget, and are physically accessible. Its authors found limitations even in advanced systems. This finding is relevant for tourism companies: a compelling digital experience can fail if the data and verification infrastructure does not support the algorithm.
There's also a tension between personalization and concentration. If systems repeatedly recommend popular options because they have more data, better reviews, or a stronger digital presence, they could reinforce already visible destinations. But AI can also be used to discover less crowded areas. Booking.com reported in 2024 that a significant portion of travelers were interested in using technology to find authentic and alternative experiences, showing that the outcome will depend on how the recommendations are designed. From Automated Itineraries to Travel Agents The next stage points toward systems capable of planning more autonomously and coordinating tasks across different platforms. Google has already incorporated AI features that allow for building personalized plans and moving toward bookings, while its research teams are working on methods that combine language models with optimization algorithms to simultaneously handle qualitative preferences and quantifiable constraints. For the tourism industry, this could transform the relationship between technology and distribution. The digital intermediary could move beyond simply displaying inventory and begin assembling a complete proposal based on budget, time, mobility, interests, and context. The opportunity lies in integrating with these systems using reliable data, up-to-date availability, and structured content. The threat arises when a business depends on a recommendation it doesn't control and whose selection criteria are constantly changing. The future doesn't demand a choice between human-driven and automated tourism. Artificial intelligence can reduce repetitive tasks and facilitate decision-making, while local expertise, verification, and professional judgment continue to provide elements that are difficult to automate. The OECD identifies opportunities for innovation alongside challenges related to data, consumer protection, employment, and the adaptation of small businesses. The competitive advantage will lie in combining algorithmic efficiency with genuine knowledge of the destination. |
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References: Google. (2025, May 20). Our vision to build a universal AI assistant . Google. https://blog.google/intl/es-419/noticias-de-la-empresa/tecnologia/nuestra-vision-para-construir-un-asistente-de-ia-universal/ Google. (2025, June 6). Optimizing LLM-based trip planning . GoogleResearch. https://research.google/blog/optimizing-llm-based-trip-planning/ Google. (2026, August 6). How Gemini plans custom trips with detailed itineraries . Google. https://blog.google/products-and-platforms/products/gemini/how-gemini-plans-trips/ Booking.com. (2024, October 16). Defying convention to deepen connections: Booking.com's nine predictions for travel in 2025 . Booking.com. https://news.booking.com/defying-convention-to-deepen-connections-bookingcoms-nine-predictions-for-travel-in-2025/ Booking.com. (2026, July 21). 68% of Colombian travelers already use artificial intelligence to plan trips . Booking.com. https://news.booking.com/es-co/el-68-de-los-viajeros-colombianos-ya-usa-inteligencia-artificial-para-planar-viajes/ de la Rosa, T., Gopalakrishnan, S., Pozanco, A., Zeng, Z., & Borrajo, D. (2024). TRIP-PAL: Travel Planning with Guarantees by Combining Large Language Models and Automated Planners . arXiv. https://arxiv.org/abs/2406.10196 Qi, J., Zhang, W., Ng, S.M., Xu, F., Li, Y., & King, I. (2026). TREK: A Travel Reasoning and Evaluation Kit for LLM Agents in Complex Trip Planning . arXiv. https://arxiv.org/abs/2607.26977 Organization for Economic Co-operation and Development. (2026, September 9). Artificial intelligence and tourism in APEC economies: Boosting innovation and enhancing sustainability . OECD Publishing. https://www.oecd.org/en/publications/artificial-intelligence-and-tourism-in-apec-economies_4549486a-en.html |
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