Experts highlight that detailed prompts and source verification are essential for AI to effectively assist travellers, emphasising control and human oversight in automated trip planning.
Artificial intelligence can be useful for trip planning, but only if travellers give it enough structure to work with. The New York Times, in an article republished by Ekathimerini, argues that generic prompts produce generic suggestions, while more detailed instructions, follow-up questions and user feedback can make the results far more practical.
The central lesson is that the chatbot should be treated less like a search box and more like a research assistant. Experts quoted in the article say travellers should describe preferences, dislikes, budget, pace and the sort of trip they actually want. KAYAK and other AI travel guides make the same point, stressing that specificity is what turns broad destination ideas into usable recommendations.
That means leading with constraints rather than vague aspirations. TripAgent and INSIDEA both recommend stating dates, trip length, spending limits, the number and type of travellers, and any hard exclusions at the outset. They also advise asking for itineraries grouped by neighbourhood, with transit times and opening hours included, so the output is easier to follow and less likely to waste time.
The article also suggests feeding AI with material you already trust. That can include notes from friends, previous research or a personal travel profile that summarises your habits and priorities. Adobe’s guide to AI travel planning makes a similar case for organising source material first, then using general-purpose chatbots or specialist tools to assemble a draft itinerary from it.
But the article is equally clear about the limits. Some travel-related sites restrict what chatbots can access, and different systems have different partnerships or blind spots. The New York Times says this is one reason travellers should ask a chatbot what sources it can actually reach, and then verify any recommendations independently rather than assuming the machine has checked everything.
Accuracy is another concern. The article describes examples of outdated listings and clearly wrong suggestions, a reminder that AI can hallucinate even when it sounds confident. That is why the best use case is not blind trust, but rapid first-pass planning followed by human checking. The most effective workflow, according to the reporting and the supporting guides, is to use AI to narrow choices, not to finalise them.
For frequent travellers, the most useful habit may be to keep a dedicated travel chat or project. The article says this makes it easier to refine plans over time, carry context from one trip to the next and store post-trip feedback for later use. In practice, the message is simple: AI can save time, but only if travellers keep control of the prompt, the sources and the final judgement.
Disclaimer: This content is intended for informational purposes only. Readers are advised to exercise their own judgement, conduct due diligence, or consult a qualified expert before acting on any information provided.
