Private Tours of Spain, a Madrid-based operator and destination management company arranging chauffeured private journeys across Spain, Portugal and southern France, has recorded a 400% increase in hyper-specific private tour requests drawn up with artificial intelligence, the company said on August 25.
The company’s revealing data points to a wider change in how international travellers approach bespoke trips, with clients handing the first stage of research to AI tools and arriving with polished day-by-day plans that operators say prize sights over the way people actually travel. It added that colleagues in France, Portugal and other European markets are seeing the same pattern backed by systems including ChatGPT, Google’s Gemini and Claude AI, which have become the biggest sytems in the west in recent years.
The plans typically arrive as detailed schedules with timings, restaurant picks and must-see lists. The company said these treat a private journey as a set of places to tick off rather than a sequence built around a traveller’s pace, interests and energy.
It cited a recent request for a six-day trip taking in Barcelona, Rioja, San Sebastián, Bilbao, Madrid, Toledo, Seville and Granada, with three Michelin-starred dinners, a private flamenco performance and an evening visit to the Alhambra. The company said the plan ignored realistic driving times and the physical demands of multi-day travel.
“The AI is not failing. It is doing exactly what it is asked to do: optimise a list of highlights. The problem sits in the prompt,” said Olivia Núñez of Private Tours of Spain. She said most people ask for the perfect collection of things to see rather than a journey matched to how they like to travel.
The company said the lists are often poorly grounded, requesting activities in the wrong month, monuments closed on the chosen day, or sunsets timed impossibly on short winter days. It said some requests carried signs of automated systems or AI agents gathering data.
It flagged a further risk that clients who delegate research to AI then disengage, handing over a brief and failing to read or respond to the proposal that follows. A single sentence about real walking pace, the company said, once conveyed more than a minute-by-minute schedule.
Núñez said the firm now keeps deep local knowledge for internal use rather than publishing it for search visibility, aiming for AI systems to recognise it as a specialist and recommend it to origin-market consultants while the detail stays with human teams.
“It is about knowing why a particular experience will be the right one for that specific traveller,” said Núñez.
The shift lands hardest on DMCs and inbound operators whose value has long sat in local knowledge published for search visibility. As travellers route their initial research through AI, the published details feed the machine, while the client arrives expecting a finished plan.
Also, operators face higher enquiry volumes with near-identical structures, more price challenges built on averages, and a real chance that clients never engage with the tailored proposal. AI searches use the same resources, including sites like Expedia, TripAdvisor, and Google Maps, to make decisions, and this would ultimately result in the systems giving potential customers similar results and ideas for visits.
How this affects on-the-ground operations is the most interesting part of the press release, as certain areas may see massive increases in footfall due to their strong SEO value, while other places not fully web-integrated won’t see as much traffic.