The conversation about Google and agentic travel keeps returning to the same question: when agentic hotel booking goes live inside AI Mode, who wins and who loses?

It is a fair question. But it is also a narrow one.

The booking moment is one point in a journey that begins weeks before arrival and ends weeks after checkout — when the experience gets processed, rated, remembered, and eventually shapes the next booking decision. Google's infrastructure touches every one of those stages. The question worth asking is what happens when Gemini becomes the interface that ties them together.

The post-pandemic rate surge gave independent hotels a comfortable story to tell. RevPAR climbed. ADR held. Occupancy came back. For several years, the top line moved in the right direction and most operators were content to watch it.

That period is over. Global RevPAR fell 5.4% among independent hotels in 2025, with ADR down 5.8%, according to Cloudbeds' analysis of 90 million bookings. The rate-led recovery has stalled. And as it stalls, something that was always true but easy to ignore is now impossible to avoid: the revenue recovery and the profit recovery were never the same thing. For a significant number of independent hotels, the profit recovery never fully happened at all.

This is not a temporary gap that will close when demand picks up. It is the result of structural cost shifts that took hold during the recovery years and show no sign of reversing. Understanding why — and changing what you measure — is the most important commercial decision an independent hotelier can make in 2026.

Agilysys outlines 30 key technology trends expected to shape the hotel industry in 2026, highlighting a shift toward more integrated, data-driven, and guest-focused operations. It argues that artificial intelligence is becoming foundational across the hotel tech stack, influencing everything from pricing and marketing to operations and guest experience. At the same time, fragmented systems are giving way to more unified platforms that enable real-time decision-making and personalization. The overall direction points toward hotels operating more like connected digital ecosystems than standalone properties.

Key takeaways

AI becomes core infrastructure: Artificial intelligence is moving from experimental use cases to a central role in revenue management, marketing automation, customer service, and operational decision-making.
Shift to platform ecosystems: Hotels are increasingly adopting integrated platforms rather than standalone tools, enabling seamless data flow across departments and improving efficiency.
Real-time data drives decisions: Access to live data is becoming critical for pricing, distribution, and operations, allowing hotels to respond faster to demand fluctuations and market changes.
Personalization at scale: Technology is enabling hotels to deliver tailored guest experiences across the entire journey, from pre-booking to post-stay engagement.

Artificial intelligence is transforming the travel journey from a series of disconnected steps into a fully integrated experience, and this shift has direct implications for hotels. The Amadeus perspective highlights how AI connects search, booking, payments, and in-stay interactions into a single, continuous flow of data. For hoteliers, this means moving beyond channel-by-channel optimization toward managing the entire guest journey as one system. Success will depend on how well hotels integrate into these connected ecosystems and use data to respond in real time.

Key takeaways

End-to-end journey control: AI is linking every stage of the travel journey, requiring hotels to think beyond distribution and manage visibility, booking, and in-stay experience as one connected process.
Shift from channels to journeys: Traditional channel strategies are becoming less relevant as AI-driven platforms guide travelers across multiple touchpoints before a booking is made.

"Since the website wasn’t designed to handle conversations, we users have learned to interact in a different way: by browsing pages, clicking links and filling out forms. And we have turned it into a habit.

But this is starting to change.

AI assistants, such as ChatGPT or Gemini, are able to understand natural language and hold conversations with users thanks to large language models (LLMs), something that, until recently, was only possible between people.

And if users can interact in real time by chatting—without having to make a phone call—, the role of the website as an interface will be threatened, as it will face increasing competition from 100% conversational channels that operate outside a browser, such as WhatsApp and, above all, the rise of AI assistants like ChatGPT or Gemini themselves. The website will remain a very important direct channel, but it will no longer be the sole point of interaction with the hotel. How will these new “direct channels” be adopted? Only time will tell."

Artificial intelligence is transforming how travelers discover and choose hotels, shifting search from a manual comparison process to an intelligent, guided experience. Instead of browsing multiple websites, travelers increasingly rely on AI to interpret their intent, filter options, and recommend the most relevant stays. This evolution reduces friction in the booking journey but also changes who controls visibility and demand. For hoteliers, the implication is clear: success will depend less on ranking in traditional search and more on being understood, structured, and surfaced by AI systems.

Key takeaways

Discovery is moving beyond traditional search: AI assistants increasingly shape which hotels travelers see and consider, reducing the role of classic keyword-based search rankings.
Visibility depends on structured and accessible data: Hotels that provide rich, well-organized content—rates, availability, amenities, policies—are more likely to be surfaced accurately by AI systems.

When OpenAI announced it was stepping back from in-chat hotel checkout, the reaction in distribution circles was relief. One less competitor at the point of transaction. The OTAs could breathe again.

That reading misses what is actually happening.

Whether or not ChatGPT processes your guest's credit card is not the question that should be keeping you up at night. The question is whether your hotel gets mentioned at all — before the traveler opens Booking.com, before they type anything into Google, before they have formed an opinion about where they are going to stay. That earlier moment, the one where a shortlist gets built and everything else gets filtered out, is where the real competition is now being decided.

Hotel marketing is not failing because of a lack of tools or channels, but because most hotels operate with fragmented guest data. While hotels collect large volumes of information across PMS, CRM, and on-property systems, this data is rarely unified into a single, actionable view of the guest. As a result, marketing remains generic, reactive, and less effective than it could be. The real opportunity for hotels is to connect and activate existing data to drive more relevant communication, stronger guest relationships, and higher revenue.

Key takeaways

Fragmented systems limit revenue growth: When guest data sits across disconnected platforms, hotels cannot build a complete guest profile, reducing their ability to personalize and convert demand effectively.
Hotels already have enough data: The issue is not data scarcity but data activation. Most hotels underutilize the data they already collect across bookings, stays, and on-property interactions.
Guest understanding remains incomplete: Without integrating data from F&B, spa, and guest feedback, hotels miss critical context that shapes guest preferences and future booking behavior.

Booking Holdings’ CEO Glenn Fogel is warning that AI platforms like Google’s Gemini and ChatGPT could reshape hotel distribution in ways that disadvantage smaller hotels. The irony is difficult to ignore. Booking.com itself played a central role in shifting power away from hotels over the past two decades, aggregating demand and becoming a dominant intermediary. Now, as AI platforms begin to sit on top of search, discovery, and booking, Booking is raising concerns about a similar dynamic unfolding again—this time with even fewer players controlling the customer relationship.

Key takeaways

A familiar pattern repeating: Booking highlights the risk of AI platforms concentrating power, echoing the same structural shift that OTAs themselves once drove in hotel distribution.
From disruptor to incumbent: Booking.com, once a challenger to hotel direct channels, is now positioned as a player potentially threatened by a new layer of aggregation.
AI as the next aggregator: Platforms like Google and ChatGPT could become the new gatekeepers, sitting above both hotels and OTAs in the customer journey.

Google is emerging as the strongest player in agentic travel, not because of better AI models but because it already owns the richest set of traveler data. Agentic AI will not replace existing booking channels but will reshape how travelers discover and choose hotels. The real shift is happening at the top of the funnel, where AI agents guide decisions before a booking is made. For hoteliers, this means Google is becoming even more central as the gatekeeper of demand.

Key takeaways

Context drives booking decisions: Google can combine search intent, email confirmations, location data, and browsing behavior to understand travelers in real time, giving it a decisive advantage in influencing hotel choice.
The battle moves to demand capture: Agentic AI changes how guests are acquired, with AI assistants increasingly deciding which hotels are shown and considered before a booking happens.
Google stays the gatekeeper: Google is unlikely to become a traditional OTA but will continue to sit between demand and supply, monetizing visibility rather than handling bookings directly.

The UK hotel sector is expected to enter 2026 with moderate growth and a sense of resilience, according to PwC’s latest hotels forecast. The report projects a 1.5% increase in revenue per available room (RevPAR) and a 1.2% growth in occupancy across UK regions. These gains are attributed to strong international demand, event-driven travel, and a steady recovery in domestic leisure travel.

However, the industry continues to face significant cost pressures, tighter profit margins, and slower rate growth. These challenges are prompting operators to seek new efficiencies and adapt to changing market conditions.

AI Adoption Among Independent Operators

Recent industry research indicates that independent accommodation providers are responding to these pressures by adopting practical, guest-facing artificial intelligence (AI) tools. These tools are generally easier to implement and can deliver value more quickly than the more complex AI systems often used by larger hotel chains.

A survey conducted by the Institute of Tourism at HES-SO Valais-Wallis, which included 1,485 hotels across six European markets, found that 41% of independent hotels are already using AI, with an additional 16% planning to adopt it. The research shows that independent hotels are primarily using AI for content generation, chatbots, and review analytics—tools that directly impact the guest experience. In contrast, chain hotels tend to focus on back-office applications such as revenue management and predictive analytics.