Visaible has launched a platform that helps hotels manage how they are presented by large language models, as the Australian company expands into the US, UK and Europe.
Its software tracks how hotels appear across AI chatbots, then updates website content, structured data, frequently asked questions and citations to improve how properties are described and ranked in answers. Hotel staff approve brand-sensitive changes, while other updates can be made on an ongoing basis.
The launch comes as travel planning shifts towards AI assistants. Research cited by Visaible from Phocuswright found 56% of US leisure travellers now use AI chatbots to help plan a trip, while Booking.com reported that 95% of Asia Pacific travellers want AI involved at every stage of their journey.
That shift is changing how accommodation is discovered online. Instead of scrolling through pages of search results, travellers increasingly receive a short list of suggested properties. That makes a hotel's position in an answer, and the accuracy of its details, more important to winning a booking.
Visaible says the commercial opportunity for operators lies in direct bookings. Hotels often pay commissions of 15% to 25% on reservations made through online travel agencies, so a guest who finds a property through an AI assistant and books direct can leave more revenue with the hotel.
Sam Rich, Founder of Visaible, said travellers are changing how they search for accommodation.
"LLMs are completely changing the way people travel. Travellers are turning to Claude or ChatGPT for advice on activities and accommodation, rather than using Google or online travel agencies," said Sam Rich, Founder of Visaible.
He said the financial impact is becoming clearer for hotel groups.
"This change in traveller behaviour has a direct commercial impact for hotels. Hotels typically pay 15-25% commission on bookings that come through online travel agencies. When a traveller books directly after finding accommodation through an LLM, that margin can stay with the hotel," Rich said.
Ranking matters
Rich said being mentioned by an AI system does not guarantee a booking. A property that appears first in a shortlist, with accurate information about rooms, amenities, location or event space, is more likely to convert than one ranked lower or described with outdated details.
"A lot of hotels assume that if they are named by an LLM, they are in good shape, but that is only half the story. What drives the booking is often where the hotel appears in the answer and whether the details are accurate enough for a traveller to act on. If the room mix, amenities, location context or event capacity are wrong, the hotel can lose the guest even when it makes the shortlist," Rich said.
Visaible already has customers in Asia and Australia. It pointed to three boutique hotels in the Auno Group that moved from being rarely cited to being consistently mentioned across ChatGPT, Perplexity and Gemini after changes were made to the content and signals those systems use.
Visaible has also tried to quantify the size of the opportunity. Based on its own modelling, it said a 150-room hotel is currently missing about USD $22,000 a month in direct-booking revenue from the AI channel, with that figure rising above USD $30,000 by 2027 if AI takes a larger share of travel discovery.
The service costs in the low hundreds of dollars per property each month, positioning it as a way for hotels to recover incremental direct bookings at relatively low cost. That pitch reflects a broader push by accommodation providers to reduce dependence on online travel agencies while preserving occupancy.
Funding push
Backed by AUD $1 million in venture funding, Visaible is now targeting overseas growth as AI-assisted trip planning gains traction beyond its home market. The expansion reflects a wider race among travel technology companies to adapt hotel marketing and distribution strategies for recommendation engines rather than conventional search.
For hotel operators, this creates a new layer of digital housekeeping. It is no longer enough to be visible on a website or booking platform if the AI systems increasingly used at the start of trip planning surface incomplete or outdated information.
The pattern is becoming harder for the sector to ignore as travellers begin their planning with a question to an AI assistant rather than a search bar.