AI for Travel Planning: What It Actually Does, and What Tourism Boards Need to Know

• The AI used in travel planning includes chatbots, dedicated AI trip planners, and AI features incorporated into booking platforms, each of which carries out a different function.
• One-third of travellers in the United States have already used AI tools at some stage of their trip planning, mainly for research and inspiration rather than for putting together a full itinerary.
• AI answer engines are able to fully deal with general questions such as "best time to visit" without requiring a click, but they still direct traffic to specific, up-to-date, or regulatory questions.
• The itineraries produced by AI are better at giving the overall outline of a trip but fall short when it comes to the specific details, the hours, the prices, and the availability.
• Tourism boards that organise their content using proper schema and provide self-contained answers are appearing in AI citations, while those that don't are losing out on visibility to third-party summaries.

Travel planning AI splits into three types, each doing a different job. 

• Chatbots that are general in purpose, such as ChatGPT or Gemini, produce a preliminary itinerary based on a user's prompt by drawing on their training data and general web knowledge rather than on up-to-date inventory information. 
• Dedicated AI travel planners, for example Mindtrip or Layla, are built specifically for itinerary construction, with mapping and saved recommendations attached.
• Finally, AI features included within the platforms that travellers are already using-such as Google's AI Overviews, TripAdvisor's trip builder, and Expedia's AI-assisted search-answer questions directly within the service that the traveller had originally opened.

This is the reason why the answer to the question 'can AI plan a trip for me' varies according to which of the three you have in mind. A chatbot is able to produce a structured draft but cannot verify that a hotel actually has rooms available on your dates.

Adoption is real but uneven. Adobe's 2026 survey of US travellers found that AI-referred visitors to travel sites spend roughly 70% longer per visit than visitors arriving from other sources, and 86% of respondents said an AI assistant improved some part of their trip planning, most often research, budgeting, or packing suggestions rather than full itinerary building. Industry estimates suggest that the AI-in-tourism market will grow by nearly 29% per year until 2030, a figure that is in line with the speed at which these tools have gone from being a novelty to becoming a habit.

The practical use cases break down by task:

1. Choosing destinations and generating ideas, narrowing down the options according to budget, season, or personal interests. This is the first and most typical application.
2. Planning an itinerary by first asking how to use AI to plan a trip after a destination has been chosen and then arranging the day-by-day schedule, the pace, and the sequencing of activities.
3. The process of creating a budget and packing is a less serious task on which AI generally does well since a mistake doesn't lead to any real problems.
4. Adjusting in real time and rerouting a journey during travel when plans change is still the most unreliable situation, since it relies on current, local information which the model does not have.

This is where AI for travel planning and destination marketing collide directly. Broad, pattern-based questions, "best time to visit Bali," general "things to do in Lisbon" lists, get fully answered inside an AI Overview or chatbot response most of the time, because the answer is already scattered across dozens of existing sources and easy to summarise. Click-through rates on searches where an AI summary appears have dropped by roughly half compared to a standard result set.

Specific questions still send a click. "Is a UK passport holder required to get a visa for Rwanda" or "Diwali 2027 dates in Jaipur" need current, precise, source-backed answers that a general AI summary is more likely to get wrong or leave vague. That gap is exactly where a destination's own content, done right, still wins the visit.

The data on this moved fast through 2026. AI referral traffic to US travel sites grew 194% year-on-year as of May, and over 2,200% since tracking started in late 2024, per Adobe's ongoing analytics research. About one-third of tourism boards report organic traffic declines of 20-30% they attribute to AI search, per Digital Tourism Think Tank's analysis, while another third report stable or growing traffic over the same period.

The visitors who do click through from AI search are worth more per visit; even where there are fewer of them, they stay longer and bounce less, though co nversion still trails standard organic traffic.

For a traveller, none of this changes how to proceed besides understanding that an AI-generated itinerary is a version and not a travel plan that is ready to be booked. For a tourism board or travel company, this change means that you need to evaluate which of your own high-traffic web pages sit in the zone "gets summarised with no clicks" versus "still leads to in-person traffic", and recreate the first one with relevant and fresh content that AI cannot easily produce. That's the same structural work covered in more depth in Melange's guide to destination marketing in tourism, and it's the first thing we audit when we start working with a new tourism board client.

If your team needs to know exactly where your content is losing visibility to AI search and what to fix first, book a strategy call with Melange Digital.

Start with a specific prompt (destination, dates, budget, pace) rather than a vague one; use a dedicated AI travel planner for itinerary structure over a general chatbot where possible; and verify every price, hour, and availability detail independently before booking anything.

AI search refers to AI Overviews, chatbot-based search (like ChatGPT or Perplexity), and generative answer engines that synthesize a direct answer from multiple sources instead of returning a list of links.

No. AI search structure and emotional destination storytelling solve different problems: one earns the practical citation, the other earns the traveller's actual interest and intent. A tourism board needs both; being structurally invisible to AI search doesn't get fixed by better brand campaigns, and better brand campaigns don't get replaced by good schema.