AI håller på att förändra hur vi väljer resmål

Writer: Co-operation partner

Choosing where to go on your next trip has long been a mix of dreams, recommendations and quite a few open tabs in the browser. Now artificial intelligence is starting to move the positions forward in the very phase where a vague idea turns into a concrete destination. The change does not mean that the classic search disappears, but it does mean that the questions can be significantly more personal from the start.

Table of contents

From keywords to a proper description

A regular search engine works best when the traveler already has an approximate language for what is being searched for. It could be a city, a beach, a hiking trail or a hotel in a certain price range. With generative AI, instead, you can start with an entire situation. A family might describe that they are looking for quiet swimming, short distances and excursions that work without a rental car, while another traveler might prioritize architecture, train connections and cool evenings.

It changes the selection process itself. Instead of first choosing a destination and then investigating whether the place is suitable, the process can be reversed. AI can sort large amounts of information based on preferences and suggest places that the traveler might not have typed into the search box on their own. Visit Sweden also describes how AI is affecting how travelers find and choose destinations by moving from lists of search results to more cohesive recommendations.

AI can sort large amounts of information. Photo: Roberto Hund / Pexels

The unexpected destination gets a second chance

The interesting thing is not only that planning can be faster. Technology can also change which places are included in the first selection. Those who previously searched for well-known weekend towns often received variations of the same established list. However, a detailed question about small coastal towns with a railway, local food market and good walking opportunities can open the door to completely different options.

The same change is recognizable from other digital environments where recommendation systems help the user sort through a large selection. This could be music, film, news or online casino, where categories and personal choices influence how content is displayed. For the traveler, the important difference is that a destination is a much more complex decision, as weather, transportation, opening hours and season can change whether a suggestion actually works. Therefore, AI is best as a starting point for further verification rather than as the final word

Inspiration still needs human detours

An algorithm may be adept at finding connections, but travel also consists of things that are difficult to express as criteria. A café that happens to be perfectly located after a long walk, a small museum that doesn't dominate search results, or the feeling of staying an extra day in a place can have great significance. These kinds of discoveries often arise through reporting, conversations, and personal detours.

This is also why reports and other sources written by people play an important role. When AI summarizes information, it needs experiences from people who have actually been there. They can provide context, nuances and practical details that help the traveler decide whether a suggestion is suitable. One example is FREEDOMtravel's report where a digital travel planner was able to set up a day in the Kingdom of Crystal – and the proposal was then tested on site.

AI needs experiences from people who have been there. Photo: George Pak / Pexels.

The best question can become more important than the top list

Travel searches are moving from short keywords to longer conversations. This means that those who can clearly articulate their priorities can also get a more useful first selection. At the same time, there is reason to check things like departure times, prices, entry rules and seasonal opening hours directly with the actor responsible for the information.

The new thing is therefore less that a machine would choose the holiday for us and more that it can broaden the starting field. A search box has traditionally rewarded those who already know the name of the place. AI can instead start with the question of how the trip should feel and work. From there, perhaps the most human part of the planning still remains: deciding which suggestion actually arouses the desire to pack the bag.