Hotels Prep for AI-Driven Discovery

The Model Context Protocol (MCP) functions as a universal translator or "USB-C for AI agents," allowing AI like ChatGPT or Gemini to directly access a hotel's live data. This open standard, introduced by Anthropic and supported by major tech companies, replaces the need for custom, one-off integrations for each AI platform. It provides a structured and secure way for AI to query everything from room availability and rates to amenities and policies. For hotels, this protocol offers a path to compete for direct bookings in an era where 37% of travelers already use AI for trip planning. With Online Travel Agency (OTA) commissions remaining high at 15%-30%, MCP allows hotels to make their direct booking information seamlessly available to AI-driven recommendation engines, potentially reducing dependence on intermediaries. This shift moves the focus from traditional search engine optimization to optimizing for algorithmic relevance in AI-powered conversational searches. Aven Hospitality, formerly Sabre Hospitality Solutions, is positioning itself as an AI-ready infrastructure partner for its 35,000+ hotel clients. By embedding MCP into its SynXis Central Reservation System, Aven enables hotels to share their data with AI platforms without needing to build and maintain their own integrations. This move is part of a broader strategy by CEO Teresa Mackintosh to modernize the platform for AI-driven commerce and reduce operational complexity for hotels. This technological shift is happening as hotels face significant operational pressures, including a 65% reported staffing shortage in North America in 2025 and an 11.2% rise in labor costs. AI is seen as a way to improve efficiency, with early deployments showing a 20% faster room cleaning process through AI-synchronized schedules. By automating routine tasks, AI allows staff to focus on higher-value guest interactions. The adoption of AI in travel is accelerating, with the market projected to grow from an estimated $2.95 billion in 2024 to $13.38 billion by 2030. This growth is fueled by changing consumer behavior; 90% of travelers are aware of AI planning tools, and among those who have used them, 63% now rely on them for most trips. More than three-quarters of these users have booked travel based on an AI recommendation, signaling a shift from browsing to delegation in trip planning. For product managers, this trend underscores the importance of structured, high-quality data. The effectiveness of AI recommendations and bookings via MCP hinges on the richness and accuracy of the hotel's information. This includes not just rates and availability, but detailed descriptions, photos, and guest reviews, which become crucial for AI analysis. Leveraging customer data from various touchpoints will be key to personalizing offers and improving conversion rates in this new landscape. User research indicates that while travelers are increasingly comfortable with AI, concerns about accuracy and real-time pricing remain. This highlights the need for robust data governance and security, especially as AI agents gain the ability to perform actions like modifying bookings or guest profiles. The focus for product development will be on creating seamless, trustworthy experiences that blend AI-driven efficiency with the potential for human interaction. Ultimately, the move towards standards like MCP is about future-proofing hotel distribution. As AI agents become more sophisticated, they will not only discover and recommend but also book travel on behalf of users. Hotels that are not structurally connected to these emerging platforms risk losing visibility and control over their customer relationships.