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Updated October 2026.
Online travel agencies (OTAs) use AI in five ways that move revenue: personalised recommendations, conversational search, 24/7 multilingual support, back-office automation and predictive demand insights. The OTAs seeing the biggest gains use AI to cut the choice overload between search and checkout. Zoover, a Dutch travel platform, reports that travellers who talk to its AI agent convert at 3x the rate of those who don’t.
Key takeaways
- Conversion, not traffic, is the OTA bottleneck. AI’s biggest lever is guiding travellers from thousands of options to a shortlist they trust.
- Travellers already expect it. 71% of consumers expect personalised interactions, and 76% get frustrated when they don’t get them (McKinsey).
- The results are measurable. Zoover: 3x conversion among travellers using its AI agent. Neckermann: +6% total bookings. Booking Holdings: about 10% lower customer-service cost per reservation after scaling generative AI.
- The large OTAs are moving fast. Booking.com, Expedia and Trip.com all run AI trip planners, and Expedia bought the AI start-up Layla in July 2026 rather than build everything itself.
The 5 use cases at a glance
1. Personalised AI recommendations that convert
AI recommendations match each traveller to a short list of relevant trips using their search behaviour, stated preferences, booking history and seasonality, instead of showing everyone the same “top-rated” list.
A five-night luxury stay in the Maldives and a last-minute weekend in Berlin are different purchases made by different people. Yet most OTAs still rely on static filters and bestseller rankings. The result is a decision problem, not a traffic problem: travellers face hundreds of near-identical options and leave to “think about it”.
What it looks like in practice:
- A traveller browsing hiking content is shown multi-day trekking tours, not city breaks.
- A family is offered the right hotel, not just any family-friendly one: activities for teenagers, but boutique rather than resort-style, because that’s what the parents asked for.
- Returning visitors see options based on what they explored last time.
Why it matters: McKinsey finds that personalisation typically lifts revenue by 10–15%, and companies that excel at it generate 40% more revenue from those activities than average players (McKinsey, The value of getting personalization right—or wrong—is multiplying).
2. Conversational search for travel websites
Conversational search lets travellers describe a trip in their own words, such as “romantic, not too touristy, under €2,000”, and get bookable results, because natural-language processing turns intent into structured search criteria.
Travellers think in feelings and constraints, not keywords. A traditional search bar returns zero results, or the wrong ones, for “a warm, cosy family beach holiday in October”. An AI search layer pulls out the destination type, travel party, budget, dates and preferences, then queries live inventory.
Two forms OTAs are using:
- Text and chat search. The traveller types a sentence instead of setting ten filters. Booking.com’s AI Trip Planner, built on OpenAI’s models, works this way inside its app, and Trip.com’s TripGenie does the same across flights, hotels and rail.
- Visual inspiration. A traveller shares a photo of a coastline, and the system identifies the place and suggests nearby hotels and itineraries. The “I want to go there” moment becomes a bookable option.
Why it matters: traveller adoption is no longer the barrier. In Phocuswright’s Europe Consumer Travel Report 2026, an April 2026 survey of travellers in the UK, France and Germany, close to nine in ten travellers who use AI say it shaped a real trip decision, from 88% in Germany to 92% in France (Phocuswright). Travellers who already plan trips in ChatGPT expect your website to understand them the same way.
3. A 24/7 multilingual AI agent for OTA customer support
An OTA AI agent is a conversational assistant built on large language models (LLMs) and trained on the OTA’s own catalogue, policies and live data. It answers travellers’ questions instantly, in their language, at any hour, and hands complex cases to a human.
Slow answers kill bookings. A traveller comparing trips at 11 pm on a Sunday won’t wait until Monday for a reply. Unlike rule-based chatbots, today’s AI agents understand context and follow-up questions.
Key capabilities:
- Grounded answers. Responses come only from your own content, product feeds and policies, so the agent recommends trips you actually sell.
- Multilingual by default. One agent serves travellers in 50+ languages without separate set-ups.
- Omnichannel. The same agent works on the website, email, WhatsApp and social channels.
- Human handover. Complex or high-value conversations go to your team with the full context.
Example: at 11 pm a traveller asks, “How fit do I need to be for this Alps hiking tour, and what gear do I need?” The agent reads the tour details, explains the fitness level (moderate, suitable for active walkers) and lists mandatory and recommended gear separately. The traveller’s last objection is answered while their intent is at its peak.
Want the deep dive on how agents move a traveller from query to booking? Read Why every OTA needs an AI agent.
4. Back-office automation for OTA operations
AI also streamlines the work behind the booking: categorising inventory, cleaning up listings, drafting follow-ups and giving staff instant answers from internal knowledge.
Practical examples:
- Auto-tagging and categorisation. AI reads natural-language tour descriptions and assigns themes, difficulty and audience, replacing hours of manual data entry.
- Listing hygiene. It flags duplicate, outdated or inconsistent listings before travellers see them.
- Lead follow-up. It drafts personalised follow-up emails and itinerary proposals from the traveller’s first conversation.
- An internal knowledge copilot. Staff, especially new hires, ask the same AI agent about products, suppliers and policies instead of searching shared drives.
5. Predictive insights from traveller behaviour and conversations
Predictive AI turns search, booking and conversation data into early signals: which destinations are rising, where travellers drop off, and which customers are about to lapse.
Every question a traveller asks an AI agent is a data point you never got from a search box: what they wanted, in their own words, and why they didn’t book.
Examples:
- Spot rising interest in European rail holidays and launch rail itineraries before competitors do.
- Find repeat customers who haven’t booked in six months and trigger a personalised re-engagement campaign.
- Find out which questions come before abandoned bookings (luggage rules, cancellation terms, accessibility) and fix the product page.
- Forecast demand by destination to plan inventory and pricing earlier.
How to get started: a 4-step rollout for OTAs
- Pick one conversion metric. Visitor-to-booking rate among travellers who use AI, compared with those who don’t, is the cleanest. Zoover measured exactly this.
- Start where the volume is. Repetitive pre-booking questions and search on your highest-traffic pages give the fastest signal.
- Ground the AI in your own data. That means your catalogue, live availability, reviews and policies. Generic models that aren’t connected to your inventory will recommend trips you don’t sell.
- Decide whether to build or buy based on maintenance, not the demo. Even Expedia acquired the AI start-up Layla in July 2026 rather than build everything itself. See AI agents for OTAs: build or buy?
Frequently asked questions about AI for OTAs
How can OTAs use AI?
OTAs use AI in five main ways: personalised recommendations, conversational (natural-language) search, 24/7 multilingual AI agents for customer support, back-office automation such as listing categorisation, and predictive insights from search and conversation data. Use cases that cut choice overload before checkout have the most direct impact on conversion.
How does AI increase OTA conversion rates?
AI increases conversion by narrowing thousands of options to a few relevant ones and answering travellers’ last questions instantly. At Zoover, travellers who interact with its Maya-powered AI agent convert at 3x the rate of those who don’t. Neckermann reported a 6% uplift in total bookings after deploying a similar agent.
What is the difference between an AI agent and a chatbot for OTAs?
A rule-based chatbot follows scripted flows and handles simple FAQs. An AI agent uses large language models to understand open-ended requests, searches live inventory, recommends specific trips, answers follow-up questions and hands over to a human when needed. That lets it guide a traveller from inspiration to booking.
How much can AI reduce customer service costs for an OTA?
It depends on query mix and how the AI is set up. Booking Holdings reported about 10% lower customer-service cost per reservation after scaling generative AI. At Zoover, about half of traveller queries are knowledge questions that the AI agent answers instantly.
Do travellers actually want to use AI when booking travel?
Yes. Phocuswright’s Europe Consumer Travel Report 2026 found that close to nine in ten AI-using travellers in the UK, France and Germany (from 88% in Germany to 92% in France) say AI shaped a real trip decision, and McKinsey reports that 71% of consumers expect personalised interactions.
Should an OTA build or buy an AI agent?
Most OTAs underestimate the ongoing cost of building: model updates, accuracy monitoring and maintenance. Expedia acquired the AI trip-planning start-up Layla in July 2026 rather than building from scratch. Buying a travel-specific platform is usually faster unless AI is your core product.
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