I’m thrilled to sit down with Katarina Railko, a seasoned expert in hospitality and a prominent voice in travel, tourism, and entertainment. With her extensive background in the industry and a passion for innovation at expos and conferences, Katarina brings a wealth of insight into the evolving landscape of hotel technology. Today, we’re diving into a groundbreaking shift in the market—how AI search platforms are transforming hotel bookings and what this means for the future of the industry. Our conversation explores the integration of AI-driven tools as a new distribution channel, the challenges hotels face in maintaining visibility, and the strategic advantages of embracing these emerging technologies.
How does the integration of AI search platforms like ChatGPT, Gemini, and Claude create a new distribution channel for hotels, and what makes this approach unique?
The integration of AI search platforms into hotel distribution is a game-changer because it taps directly into how travelers are now planning their trips. These platforms, like ChatGPT, Gemini, and Claude, are becoming go-to tools for research and decision-making. By connecting hotel availability, rates, and inventory to these AI systems through innovative protocols, hotels can appear organically in search results at the exact moment a traveler is looking for options. What’s unique here is the seamless, direct connection that bypasses traditional intermediaries, allowing hotels to present their rates without the added layers or costs often associated with other booking channels. It’s about meeting guests where they are in this digital evolution.
What is the Model Context Protocol, and why is it critical for connecting hotels to AI search tools?
The Model Context Protocol, or MCP, is essentially a standardized framework that allows AI models to securely and efficiently interact with external data sources, like hotel booking systems. Think of it as a translator that ensures AI platforms can access and display real-time hotel information—rates, availability, and more—in a consistent way. Its importance lies in creating a reliable bridge between two complex systems, making sure that when a traveler asks an AI tool for hotel options, the data pulled is accurate and directly from the source. Without something like MCP, there’s a risk of outdated or incomplete information, which could frustrate users and hurt a hotel’s credibility.
What trends in traveler behavior or technology prompted the focus on AI search for hotel bookings at this moment?
We’re seeing a significant shift in how people approach travel planning. More and more, travelers are turning to conversational AI tools for quick, personalized recommendations. They’re asking questions like, “What’s the best hotel near this landmark?” and expecting instant, tailored answers. This trend is growing rapidly because these platforms simplify the research process, pulling together insights in a way traditional search engines often can’t. On the tech side, AI models have advanced to handle complex queries and integrate with live data, making now the perfect time to position hotels within this space before it becomes oversaturated or dominated by other players.
Why is it such a challenge for hotels to maintain visibility in AI search results compared to traditional methods?
The challenge with AI search results is that they often prioritize listings from online travel agencies, or OTAs, over direct hotel offerings. Unlike traditional search engines where hotels can optimize for visibility through SEO or paid ads, AI platforms use algorithms that may not inherently favor direct sources. This means a hotel could be completely overlooked at the critical decision-making stage, even if they have better rates or availability. It’s a different playing field—one where hotels need new strategies to ensure they’re not just visible, but also competitive against the aggregated listings that AI tends to surface first.
How does the current bias toward OTA listings in AI search platforms impact hotel owners, and what are the broader implications?
The bias toward OTA listings is a real pain point for hotel owners because it drives up costs and dilutes direct relationships with guests. When travelers book through OTAs, hotels pay hefty commissions, which cut into profit margins. Beyond that, they lose the opportunity to own the customer journey—gathering data, building loyalty, or upselling services. The broader implication is a potential over-reliance on intermediaries, which can limit a hotel’s control over pricing and branding. If this trend continues unchecked, smaller or independent hotels might struggle even more to stand out in a crowded digital marketplace.
In what ways can hotels reclaim visibility on AI search platforms without ramping up their marketing budgets?
Hotels can reclaim visibility by leveraging direct integration with AI search platforms, ensuring their rates and availability are surfaced organically during traveler queries. This approach doesn’t require additional ad spend or complex campaigns; it’s about embedding their data into the AI ecosystem through secure protocols. By focusing on direct bookings in this space, hotels can present their best offers without the middleman, maintaining control over pricing and guest interactions. It’s a cost-effective way to compete, especially since it complements existing digital strategies rather than replacing them.
Can you share some details about early testing programs for AI search integration and what kind of hotels might benefit most from participating?
Early testing programs for AI search integration are designed to bring select hotels into the fold as pioneers. These beta phases focus on a mix of properties—large chains with robust systems as well as boutique or independent hotels looking to expand their reach. The goal is to test how AI-driven bookings perform across different markets and property types, refining the technology based on real-world data. Hotels that join early can help shape the platform while gaining first-mover advantage, learning how to optimize their presence before AI search becomes mainstream.
What specific advantages do you think hotels will gain by being part of these initial AI search beta groups?
Being part of initial beta groups offers hotels a front-row seat to innovation. They get early access to data on how travelers interact with AI search—things like click-through rates or booking patterns—which can inform broader marketing strategies. There’s also the benefit of visibility; being among the first to appear in AI results can set a hotel apart from competitors still playing catch-up. Plus, participants often receive direct support from tech providers to fine-tune their integration, ensuring they’re maximizing every opportunity this channel offers.
How do you envision AI search shaping the long-term future of the hotel industry?
AI search has the potential to redefine how hotels connect with guests over the long term. It could streamline the booking process into something hyper-personalized, where travelers get recommendations based on nuanced preferences without sifting through endless options. I believe it will shift power back to hotels that adopt early, allowing them to build direct relationships and reduce dependency on intermediaries. As AI becomes more embedded in daily life, it might not just complement but eventually dominate traditional booking methods, especially for younger, tech-savvy generations who already rely on these tools.
What is your forecast for the role of AI-driven bookings in the hotel industry over the next decade?
Over the next decade, I foresee AI-driven bookings becoming a cornerstone of the hotel industry. As these platforms evolve, they’ll likely account for a significant share of reservations, especially as trust in AI recommendations grows among travelers. Hotels that invest in this space now will have a competitive edge, with stronger direct booking channels and deeper guest insights. My forecast is that we’ll see a hybrid model emerge—traditional methods won’t disappear overnight, but AI will increasingly influence discovery and decision-making, pushing hotels to adapt or risk falling behind.
