David has a friend who planned a Scandinavian trip around the same time. The friend used ChatGPT. He researched the same kinds of questions David did, such as logistics, accommodations, and activities, and assembled them into what looked, on paper, like a thorough itinerary. What he did not know, and what the AI could not tell him, was that a small regional airport in that part of Sweden is served by private jets that land some distance from any taxis or rental cars. His friend arrived and had no way to get to his destination. Add to that, one of his accommodations was under construction. These are not obscure failures, but rather the ground-level details no algorithm can capture because they are not uniformly published, do not rank in searches, and change faster than any training data can track.
David's specialist knew this. Not because she had read about them, but because she has relationships with local operators who tell her when something changes. That is a fundamentally different category of knowledge; not a better database, but a more immediate, experience-driven intelligence. "A travel specialist has the knowledge you need," David said. "And I'm at a point in my life where I just don't want any problems."
He also has a larger concern about the trajectory of AI travel planning. He watched it happen in another industry: a platform offers something useful, free, people get hooked, and then the business model quietly shifts toward whoever is willing to pay for placement. "Will hotel companies start paying AI companies to promote their hotels?" he asked. "That is the real fear. It's already how Google search works, and most people don't realize it." For a traveler who wants recommendations based on his interests rather than someone else's, the distinction matters.







