Travel was one of the first industries transformed by the internet — online booking, price comparison and reviews. AI is now reshaping it again: in how prices are set, how trips are planned, how hotels and airlines serve guests, and how travelers move through airports.

Pricing and revenue management

Airlines pioneered revenue management decades ago, adjusting fares based on demand, timing and remaining seats. Hotels, car rental companies and online travel agencies followed. Machine learning now forecasts demand more precisely using search data, events, competitor prices and booking patterns, adjusting prices continuously.

For travelers, this means prices can change frequently. Booking flexibility, price alerts and comparing dates remain the best defenses.

AI trip planning

Travelers increasingly ask AI assistants to suggest destinations, build itineraries, estimate budgets and find activities. Travel companies have integrated AI assistants into their apps and websites, and some AI assistants can search flights and hotels directly. The next step is agents that book complete trips within a budget and preferences you set.

Assistants are good at inspiration and structure, but they can be wrong about opening hours, visa rules, prices and distances. Verify important details with official sources.

Customer service — and a legal lesson

Airlines, hotels and travel agencies use chatbots to handle bookings, changes and questions. A widely cited case shows the responsibilities involved: in Moffatt v. Air Canada (2024), a Canadian tribunal ruled that Air Canada was liable for incorrect information its website chatbot gave a customer about bereavement fares. The airline had argued the chatbot was responsible for its own actions; the tribunal rejected that, holding the company responsible for all information on its website. Companies are accountable for what their AI tells customers.

Hotels and hospitality

  • Operations: forecasting occupancy to plan staffing, housekeeping and food purchases.
  • Personalization: remembering guest preferences and tailoring offers.
  • Guest messaging: answering questions, taking requests and translating between languages.
  • Energy management: adjusting heating and cooling based on occupancy.
  • Reviews: analyzing guest feedback at scale to find recurring issues.

Airports and borders

Biometric boarding and automated border gates use facial recognition to verify identity. AI also manages baggage flows, predicts queue times and optimizes gate assignments. Privacy concerns center on consent and how long biometric data is retained.

Language and accessibility

Real-time translation in apps and earbuds helps travelers communicate. AI also supports accessibility, for example describing surroundings for blind travelers or providing captions.

Concerns

  • Fake reviews generated with AI undermine trust in platforms.
  • Opaque pricing and potential price discrimination.
  • Overtourism: AI recommendations can concentrate visitors in the same popular places.
  • Errors in AI travel advice, from closed attractions to wrong visa information.

What travelers can do

  • Use AI for inspiration and structure, then confirm key details on official websites.
  • Set price alerts and compare dates instead of booking at the first price you see.
  • Read a sample of individual reviews, especially recent and detailed ones, rather than relying only on summaries.
  • Save chatbot conversations about bookings, refunds or policies in case of disputes.
  • Check biometric options at airports and whether they are optional.
  • Consider less-visited alternatives suggested by AI to avoid crowds and support local economies.

Behind the scenes: hotel operations

A mid-sized hotel using AI might forecast occupancy and restaurant demand weeks ahead, schedule housekeeping and kitchen staff accordingly, adjust room prices daily based on local events and competitor prices, answer guest messages in many languages, and analyze reviews to find recurring complaints such as slow check-in or noisy rooms. Each of these uses is modest, but together they can improve margins in an industry with high costs and seasonal demand.

What to watch next

  • AI agents that book full trips end to end.
  • Consumer protection rules for AI customer service.
  • Biometric travel programs expanding across airports.
  • Platforms’ measures against AI-generated fake reviews.

Key takeaways

  • Machine learning powers dynamic pricing across airlines, hotels and rentals.
  • AI trip planners help with inspiration but need fact-checking.
  • In Moffatt v. Air Canada (2024), the airline was held liable for its chatbot’s wrong advice.
  • Hotels use AI for forecasting, personalization, messaging and energy management.
  • Fake reviews, opaque pricing, overtourism and errors are concerns.

Frequently asked questions

Can I trust an AI itinerary?

Use it as a draft. Check opening hours, travel times, prices, entry requirements and safety information with official sources.

Are companies responsible for their chatbots’ answers?

In the Air Canada case, the tribunal said yes: the company was responsible for information provided by its chatbot.

Do prices change because I searched before?

Prices change mainly due to demand and availability. Practices around personalized pricing vary and are regulated differently across countries.