One day AI nailed my trip, the next it missed completely. That contrast pushed me to ask a harder question: how do we build an AI that actually helps travellers, not just sometimes, but reliably?
Two cities, two outcomes
In March I tried AI for my first time in Madrid. From my hotel location it mapped a walking route, suggested what to see, where to eat, where to slow down. It felt like a calm local guide and it saved me hours.
A few days later in Barcelona, a city I know very well, AI gave me only the obvious. Top tourist spots, nothing fresh, nothing that matched my context. Inspiration without relevance turns into frustration. That gap is exactly the problem we need to solve.
What travellers really need
Holiday planning often shifts from excitement to stress. Families juggle school holidays, budgets and apartment sizes. Older travellers want predictability, trustworthy details and time to decide. AI promises to reduce the cognitive load, to cut through noise, to surface options that fit the person, the place and the moment.
We already see experiments everywhere. Expedia can transform even an Instagram Reel into a trip itinerary. Webjet scans thousands of flights and instantly finds the best routes. GuideGeek answers questions through WhatsApp and Messenger. Some agencies in the UK are even testing AI call-handlers that talk directly to customers. All of these tools share the same ambition: to make decisions smoother and reduce stress.
From lesson to plan, where to begin
Here is the build plan I would start with if the goal is AI that truly helps travellers.
Start with pull, then earn the right to push
Begin with a conversational helper that answers real questions, from real locations and dates. Add proactive suggestions only after you prove usefulness.
Ground every answer in local context
Use the traveller’s anchor points: hotel or resort location, dates, mobility, party size, budget range, weather window, opening hours, seasonality, school holidays.
Balance data and curation
Inventory what you already have, then add what you must have.
- First party: accommodation details, availability, amenities, pricing ranges, FAQs, on-site services, accessibility notes.
- Trusted external: transport, events, weather, trails, museums, eateries with hours and reservations, school holiday calendars.
- Curate a “beyond the obvious” layer for each destination, even if it is small. Quality beats quantity.
Design the decision, not just the list
Return short, actionable cards with a clear next step.
- Each card: what it is, why it fits this person now, how far it is, how to book or save.
- Offer a route or mini-itinerary by default, not scattered items.
- Let users tune results with one-tap filters.
Build trust into the UI
The interface should feel like a natural extension of the brand the traveller already knows. Tone of voice, CTAs and visual language must be consistent with the brand experience, so that AI does not introduce a new “system” the user has to learn. Every suggestion should clearly state why it was made, in a single, transparent line. Expectations must be explicit: what AI can do, and what it cannot. No false promises, no surprises. Trust is built not only by accuracy but also by clarity and brand continuity.
Respect human limits
AI should reduce cognitive load, not increase it. Calls to action must be predictable and action-oriented, aligned with brand voice. Accessibility is non-negotiable: respect WCAG standards, design heuristics, and inclusive interaction patterns.
The goal is to help the user focus on the decision itself, not on understanding how the AI works. When expectations are clear and the experience is seamless, trust follows naturally.
Make quality measurable from day one
Track signals that prove usefulness even if bookings happen elsewhere.
- Inspiration rate: Did the traveller save an idea, share it with someone, or add it to their plan?
- Relevance: Did they keep the suggestions or throw them away? If they asked for more details about the same plan, that shows the AI was on the right track.
- Stress reduction: After using it, does the traveller feel calmer or more confused?
- Discovery: Did the AI help them find something they wouldn’t have discovered alone?
- Handover: Even if the booking happens elsewhere, did the AI nudge them into the next step, like clicking through to a website
The path forward
My takeaway from Madrid and Barcelona is practical. AI is not a magic crystal ball. It is useful when it removes friction, respects context and earns trust. If we start with pull, ground answers in the traveller’s reality, measure usefulness beyond bookings and keep suggestions explainable, we can build an assistant that feels less like a “nice-to-have” feature and more like a companion. When that happens, the last click can stay wherever the traveller prefers. The value of AI will be the calm it brings to the journey.