June 17, 2026

💻 In two years, ChatGPT reached approximately 400 million weekly users. Three out of four smartphone owners now routinely use voice assistants. This reveals a rapid shift in how people obtain information, emphasizing plain-language answers over traditional methods. Businesses, still reliant on outdated systems, face a growing disconnect as employees experience seamless AI responses at home. Access to dashboards and reports fails to meet expectations for quick answers, highlighting a behavioral shift in information retrieval.

📈 June 16, 2026, Steinhausen, Switzerland — RoomPriceGenie, used by over 4,000 hotels globally, unveiled an enhancement to their revenue management system. The new feature, price explanations, offers hoteliers transparency in rate recommendations by detailing market conditions, demand signals, and property settings. This helps identify pricing constraints, enhancing revenue opportunities. CEO Chas Scarantino emphasizes that understanding recommendation logic empowers hoteliers to maximize RMS benefits. Meet RoomPriceGenie at Booth 951 at HITEC San Antonio for more.

🏨 In a conversation on Hotel Moment, Wilhelm Luxem, with a 50-year career in luxury hospitality, emphasizes technology's role in enhancing service. His approach includes a two-week training rule and addressing the demand for personalized experiences, aiming to maintain authentic human connections. Karen Stephens, Revinate's Chief Marketing Officer with over 25 years in hospitality tech, hosts the podcast. In her current role, she led Revinate to its highest booking quarter in Q4 2023.

💻 In 2026, hotel discovery pivots from keyword searches to AI-driven conversational queries. More travelers ask AI for specific stays like "a rooftop stay for Sunday" or "family-friendly near theme parks." This shift, highlighted by Jason Cincotta, means AI visibility is crucial for hoteliers through structured, machine-readable content. Large language models like ChatGPT influence recommendations, making traditional search strategies evolve. Model Context Protocol (MCP) emerges as a vital consideration in this new booking landscape.

What happens when travelers stop searching with keywords and start asking AI for the “right” hotel? How will properties stay visible when discovery, distribution, and booking are increasingly shaped by conversational search? Inspired by a recent webinar, AI & Hospitality: How hotels get found in 2026 , this article explores what that shift means for hoteliers, and why Model Context Protocol (MCP) could play a role in the next phase of the booking journey. The front door to hotel discovery is changing For years, hotel discovery followed a familiar pattern. Travelers typed in a few keywords, scanned a list of results, compared ratings and prices, and eventually chose a booking path. That pattern is now beginning to shift. More travelers are turning to AI assistants and conversational tools to ask more specific questions that reflect intent, context, and personal preferences. Rather than browsing broadly, guests increasingly describe what they want and expect the system to interpret it. This shift matters because it changes the rules of visibility. Instead of competing only for broad phrases like “boutique hotel in Barcelona,” hotels can surface for requests such as a rooftop stay for a Sunday night, a family‑friendly property near a theme park, or a hotel with a distinctive experience that matches a guest’s travel style. Jason Cincotta summarized this shift simply: “The long tail is now mainstream.” Traditional search is not disappearing, but AI‑driven discovery creates new opportunities for hotels to appear in response to richer and more specific guest needs, rather than being grouped into broad, undifferentiated categories. Watch the full conversation: AI & Hospitality: How hotels get found in 2026 What LLMs really mean for hoteliers Large language models sit behind the conversational tools many travelers already use, including ChatGPT and Gemini. For hoteliers, the technical mechanics matter less than the practical outcome: these systems increasingly influence which properties are mentioned, recommended, or excluded before a guest ever clicks on a website. In this environment, AI visibility becomes the next evolution of search visibility. Discovery is shifting away from ranked links and towards curated answers, where structured and trusted information is essential to being surfaced at all. As Jason noted during the discussion, LLMs are already approaching the point where they can “name hotels and the website of that hotel without ever using a web search.” That does not mean traditional search behavior disappears overnight, but it does make AI discoverability an immediate distribution consideration. AI visibility is not separate from search strategy. It is the next stage of it. The same discipline that once focused on crawlers and ranking signals now needs to account for machine‑readable content, accurate descriptions, availability, amenities, policies, and the details that make a property worth recommending. If a hotel cannot be clearly understood by an AI system, it becomes far harder to surface in an AI‑driven journey. MCP is more than a buzzword One of the most important concepts discussed in the webinar was Model Context Protocol, or MCP. At a practical level, MCP