Imagine telling your phone that you want a quiet boutique hotel near a city centre, below a certain price, with a decent breakfast and late checkout. A few seconds later, an AI assistant compares the options, explains why each one fits and helps complete the booking. This is no longer hypothetical.
Authors
- Faizan Ali
Established Professor of Marketing and Vice Dean (Startegic Projects), University of Galway
- Laiba Ali
Lecturer, Hospitality and Tourism, University of Sunderland
In late August this year, Google began rolling out hotel booking through its AI Mode search feature in the US. Travellers can describe their preferences conversationally, compare hotels and guest reviews, select a room, check cancellation conditions and complete the booking using Google Pay. Partners include Booking.com, Expedia, Hilton, Marriott and IHG, the parent company of Holiday Inn.
The traveller still confirms the transaction. But that final click can obscure how much of the searching, comparing and decision-making has already been delegated to agentic AI.
This points to a significant change in how artificial intelligence may shape travel. AI is moving from systems that mainly answer questions towards systems that can increasingly interpret goals, make decisions and take action.
From answering questions to taking action
Hotels have used chatbots and recommendation systems for years. Most are reactive: a guest asks when breakfast starts, and the chatbot provides the answer. A traveller enters dates and preferences, and a booking site recommends suitable hotels.
Agentic AI goes further. These systems can operate with greater autonomy, adapt to changing circumstances and coordinate actions across different systems with less continuous human direction. This distinction is central to research we conducted on agentic AI in hospitality and tourism.
We identify five broad roles that such systems could perform, ranging from guest-facing service and itinerary planning to monitoring operations, managing engagement and coordinating multiple systems.
Consider a disrupted holiday. A conventional chatbot might tell you that your flight has been cancelled. A more agentic system could identify alternative flights, assess how the delay affects your hotel booking, modify airport transport and rearrange activities while retaining your preferences.
The important change is therefore not simply that the AI becomes better at conversation. It is that more decision-making authority is delegated to the system.
A different kind of risk
The commercial appeal is obvious. Travel businesses can respond around the clock, reduce repetitive work and offer much more individualised services.
But autonomy changes the consequences when AI gets something wrong.
A useful warning comes from Air Canada. In 2022, its chatbot incorrectly told a passenger that he could retrospectively claim a bereavement fare. When the company later refused the refund, it argued before a Canadian tribunal that the chatbot was effectively responsible for the information it had provided. The tribunal rejected that argument and held Air Canada responsible for information presented through its website.
That system was a relatively simple chatbot, not today’s agentic AI. But this is precisely why the case matters. If accountability became contested when AI merely supplied incorrect information, the stakes become higher when systems start taking actions on behalf of customers.
Bias creates a similar problem.
A voice-based concierge may understand some accents more reliably than others. A recommendation system might assume that an older traveller wants only sedentary activities, or infer dietary or cultural preferences from crude proxies rather than what the guest has actually requested. These are risks already identified in hospitality research .
When AI merely recommends something, a traveller can reject the suggestion. When it begins acting on such assumptions, bias can potentially influence which offers are presented, how complaints are handled or how services are personalised.
What happens to the human employee?
The same shift matters for hospitality workers.
AI can remove repetitive tasks and allow employees to spend more time on interactions requiring empathy, creativity and judgment. But it can also constrain employee discretion or become a mechanism for reducing staffing costs.
Our research therefore treats workforce displacement and role change as one of the central risks of agentic AI.
The relevant question is not simply whether AI will replace hospitality jobs. It is which decisions businesses choose to automate, and which they deliberately leave with people.
That distinction matters in an industry where the value of a service often depends on responding appropriately to unusual, emotional or culturally sensitive situations.
The questions travellers should start asking
Regulation is also evolving. Most provisions of the EU AI Act became applicable in August this year, although some requirements for high-risk systems will take effect later.
But regulation alone will not determine how comfortable people are with increasingly autonomous travel systems.
As AI becomes embedded more deeply in booking and hospitality, travellers may need to ask three simple questions: What is this system allowed to decide for me? What information is it using to make that decision? And can I easily reverse the decision or reach a human if something goes wrong?
For hotels, airlines and travel platforms, the corresponding question may be even more important: When an AI acts on your customer’s behalf, who remains accountable for the outcome?
The companies that answer that question clearly may ultimately gain more than operational efficiency. They may gain something considerably harder for an AI algorithm to generate: trust.
