The fastest shift in travel behavior just became the default

This article was written by Phocuswright. Click here to read the original article

This article was written by Phocuswright. Click here to read the original article

Distribution power is shifting through regulatory and platform decisions rather than technological advances. Google's response to EU antitrust regulation is restructuring how hotels appear in search results, while OpenAI's decision to redirect bookings away from ChatGPT surfaces the operational complexity of closing transactions within conversational interfaces. The gap between AI experimentation and execution continues to widen. Hotel Search Visibility Tilts Toward OTAs Under Google's DMA Compliance Google's implementation of Digital Markets Act requirements is restructuring visibility in hotel search results, with direct booking channels and intermediaries experiencing changed prominence in rankings. The shift reflects regulatory intervention in search market dynamics rather than competitive product improvements → analysis examines how DMA compliance redistributes search visibility . OpenAI Redirects ChatGPT Bookings to Third-Party Platforms OpenAI stepped back from handling bookings directly within ChatGPT, redirecting transactions to third-party platforms instead. The decision underscores the operational weight of managing payments, cancellations, refunds, customer support, compliance, and inventory synchronization—each running on disconnected systems. OTAs gained market value immediately as investors interpreted the move as threat removal → viewpoint questions whether conversational booking faces structural limitations similar to Google's metasearch challenges . AI Experts Address Implementation Gaps at Female Founders Summit Hospitality AI practitioners emphasized solving business problems first, establishing data governance frameworks, and creating dedicated experimentation time for teams at the Female Founders in Hospitality Summit. The guidance reflects growing recognition that AI adoption requires operational discipline beyond selecting tools → lessons from summit highlight practical implementation challenges . Signals Lighthouse Pricing argues real-time rate shopping data provides competitive advantage over scheduled collection methods that lag market changes by hours. RDP announced 2026 roadmap enhancing PMS capabilities with deeper cloud integrations and expanded timeshare modules addressing staffing shortages. Accor and Risma strengthened Moroccan partnership launching Sofitel Tangier and co-funded training academy ahead of 2030 World Cup. Wyndham crossed 100-hotel threshold in Mexico nearly doubling footprint in five years through strategic partnerships. HotelRunner maintained 98% connection health and top 10 booking ratings on Agoda after 15 years collaboration. People Olivier Eynard joined Raffles Hotels & Resorts and Fairmont Hotels & Resorts as Global Vice President, Food & Beverage, bringing 20 years experience from RIKAS Hospitality Group, The Arts Club, and La Petite Maison to oversee 121 hotels. Andrew Insch was appointed CFO of Aethos with focus on building financial infrastructure for Europe's fastest-growing lifestyle hospitality brand expansion. Daniel Lofton joined OUTRIGGER Hospitality Group as Vice President of Hawai'i Revenue Strategy after founding team role at Duetto Research. Properties New pipeline signings include Holiday Inn Express Surat Gauravpath marking IHG's entry into Gujarat's commercial hub, Kilchoan Estate by Dunton opening June in Scottish Highlands, BLESS Ibiza The Site expanding luxury collection, and SONO Belle Hanoi Old Quarter . LEVA Casablanca rebranded as LEVA Hotels enters North Africa. Hotel Viking in Newport completes multimillion-dollar renovation ahead of May reopening. Recent openings include The Hôtel Lili from Palisociety in Beverly Hills and Punthill Narrabundah expanding Veriu Group's ACT footprint.

VAIL, Colo. — April 7, 2026 — Resort Data Processing (RDP), a long-time provider of property-management system (PMS) technology for resorts, hotels, and timeshare properties, is committed to helping lodging owners and operators adapt to rising operational complexity, labor challenges, and increasing guest expectations through purpose-driven innovation. Guided by the company’s 2026 Technology Roadmap, RDP users are gaining access to deeper cloud capabilities, broader hotel technology integrations across the hospitality technology ecosystem, and smarter automation designed to help them accomplish more with fewer resources. “Guest communication is becoming more digital and immediate, and travelers increasingly expect seamless messaging, quick responses, and self-service options such as mobile check-in and check-out,” said Ron Stahl, Development Manager at RDP. “At the same time, resorts are under pressure to maximize revenue through dynamic pricing while also managing staffing shortages and rising operating costs. “Our roadmap was built to help resorts and hotels do more with less while still delivering a high-quality guest experience,” he said. “It simplifies their technology stack, automates routine work, and connects the systems they rely on day to day. But rather than just focusing on today’s problems, we’re giving operators tools that support their long-term strategy.” Improving Connectivity, Communication & Departmental Coordination A major focus of RDP’s 2026 Technology Roadmap is improving connectivity across systems. Many operators still struggle with fragmented technology platforms that do not easily communicate with each other. RDP is prioritizing deeper integrations and a more cohesive environment, so operators can manage reservations, guest engagement, payments, and operations more smoothly within a connected hospitality ecosystem. “RDP has a strong presence in the resort, timeshare, and fractional ownership markets,” Stahl said. “As such, we are also expanding the capabilities of our Owner Portal to help properties with complex ownership models communicate more effectively with proprietors and manage shared-use properties more effectively. In addition, RDP is introducing new enhancements to its timeshare and fractional ownership modules in 2026, giving operators more robust tools to manage ownership structures, reservations, and communications.” Prioritizing Revenue Growth Revenue growth remains a key priority for operators. RDP’s roadmap reflects this with enhancements designed to support stronger performance metrics such as RevPAR, GOPPAR, and total revenue per available room (TRevPAR). By connecting operational data, guest insights, and revenue tools more effectively, the platform helps properties make smarter decisions that improve both guest satisfaction and financial outcomes. “We spend a lot of time listening to operators about what’s changing in their businesses,” Stahl said. “What we’re hearing is a clear need for consolidated platforms, more automation, and technology that truly understands the complexity of resort operations. Our 2026 roadmap reflects what our customers are asking for and ensures they are prepared for the future.” With this forward-looking approach, RDP aims to reinforce its role as a long-term technology partner for resorts and hotels navigating an increasingly complex industry. By aligning product development with real operational challenges and long-term industry trends, the company’s roadmap demonstrates a clear vision: helping hospitality operators run more efficient, connected, and profitable

AI overload is real. Eye-watering data points, a plethora of shiny tools, and enough confusion to make any hotelier's head spin. And yet, buried underneath all that noise is a signal most hotel marketers are flat-out missing. Your guests aren't Googling anymore. They're prompting. And if your hotel isn't showing up in those answers, you don't have a visibility problem ... you have a revenue problem. I recently sat down with Craig Carbonniere , a senior marketing strategist at Milestone Inc . and one of the sharpest minds in hospitality AI (the guy was presenting on AI to hoteliers back in 2016, before most of us even knew what a large language model was). He shared some incredible data that should be stapled to every hotel marketer's wall. AI Discoverability for Hotels Here's what every hotel marketer and revenue manager needs to hear right now. The Curve Nobody Saw Coming (Until It Was Already Here) Milestone has been tracking AI-driven referral traffic across 3,500 hospitality websites since January 2024. The growth curve Craig showed me didn't slope. It spiked. The kind of chart that makes you do a double-take and close your other browser tabs. "The last time we saw this kind of pattern," Craig told me, "was really when smartphones were introduced." We all know how that movie ended. Today, more than half of all hotel website traffic comes from mobile. Milestone's data projects that nearly half of all hotel website traffic will soon arrive via AI engines: ChatGPT, Google Gemini, Perplexity, Claude, and whatever drops next month. This isn't a forecast anymore. It's already happening. At our agency, 20 to 30 percent of inbound group sales inquiries (when clients self-report the source) are coming directly from AI tools. ChatGPT leads the pack. And it's trending up every single month. The habit loop is already locked in. Recent research shows that 63% of AI users * rely on it for most or all of their trips. Once someone uses AI to research travel, they almost never go back to the old way. It's that good. I know because I've replaced my insurance comparisons, my financial planning research, and half my life admin with it. It's addictive. And your future guests are already hooked. Your Hotel Is Invisible and Doesn't Know It Getting buried on page two of Google stings. But at least you're still in the game. Being invisible to an AI recommendation engine means there's no consolation prize. You simply don't exist. And the segment driving this shift? It's not just seasoned meeting planners on Cvent. It's the executive assistant who just got voluntold to plan the company off-site. The office manager booking a leadership retreat for the first time. The non-professional planner who has never heard of an RFP and has zero interest in calling a hotel sales rep. They have a browser, a prompt bar, and absolutely no patience for friction. They're typing things like: "I need a resort in San Diego for a 50-person corporate

You know there is going to be an influx of demand and your competitive set could already be adjusting rates. You decide to run a rate shop but the data you’re looking at with your current provider is from yesterday. And herein lies the problem for many revenue managers. Rate shopping is the most frequently used function in hotel pricing and market intelligence tools, and as revenue manager you will know it’s essential for making correct pricing decisions that drive room revenue. But across most intelligence platforms, the data presented isn’t what the market looks like right now. It’s a historical snapshot, taken hours ago, or overnight, stored and displayed on demand. In a hospitality world where booking windows are compressing and same-day demand swings are the norm, that gap between ‘when the data was collected’ and ‘when you need to act’ can really cost you. What is a live rate shop? A live rate shop is an on-demand, real-time competitor rate check that pulls current pricing directly from all channels with no delay, no scheduled window, and no additional fee. You see live market data as it stands, at the moment you look. Why most rate shopping tools rely on cached or scheduled data Understanding this limitation starts with understanding how most rate intelligence solutions work. The majority of rate shopping tools collect competitor data through scheduled scrapes. These are automated processes that pull and store room prices at fixed intervals. This could be every few hours, overnight or more. The timing depends on the tool and the plan. With these tools when you open the dashboard, you’re not seeing the live market. You’re seeing the last stored version of it. Some tools allow you to trigger a manual refresh, but this often comes with stipulations such as a wait time, a credit from a monthly allowance, or an upgrade to a higher pricing tier. In practice, you learn to work around this, timing shops for key decision windows and accepting that the data in between is a best estimate. Scraping live data at scale across thousands of OTA listings is computationally expensive, so from the provider’s point of view, you can see why many don’t want to offer live rate shops. But the cost is passed directly to you in the form of data that may not reflect the market they’re actually pricing into. The consequence is most obvious in fast-moving revenue situations. A competitor drops rates by 15% at 11am. Your next scheduled shop runs at midnight. For 13 hours, you’ve been pricing against a market that no longer exists. Alternatively, a surge event pushes demand sharply upward and without a live view of how your comp set has responded, you either follow too late or miss the window entirely. Here’s a snapshot of how the two rate shopping approaches compare: What a real-time live rate shop actually means and why it wins out over the other options Live rate shopping closes the gap between what’s actually

Stephanie Smith of Cogwheel recently joined an incredible panel at the Female Founders in Hospitality Summit in New York , moderated by Saadiq Rodgers-King, an AI Transformation Consultant , alongside Kim Bennett of AtlasGuru and Katrina Stalcup of Fora Travel . Here were a few of my biggest takeaways from the discussion. Start with the Problem, Not a Tool One of the biggest reasons AI pilots fail is that companies start with technology instead of a business problem. I see this pattern over and over in my consulting work. Organizations say ‘We need an AI strategy.’ But what they actually need is clarity on what problem they’re solving. The intent you bring determines what you get out of it. Saadiq Rodgers-King Across the panel, the most successful examples of AI adoption came from solving clear operational challenges—whether that was scaling travel advisor support, generating travel itineraries, or analyzing hotel marketing performance. AI is not a strategy; it’s an accelerator. If you don’t know where you’re going, it just gets you lost faster. Kim spoke to the lessons learned from building a consumer travel platform and evolving it into an AI-powered B2B product. It turned out the bigger business problem to solve was that travel companies are sitting on enormous content libraries with no scalable way to turn them into actionable trip plans with a high-quality, traveler-friendly UX that goes far beyond what a chatbot can offer. The AI use case became much cleaner, the customer much clearer, and the value proposition much easier to articulate. The lesson for us was about not falling in love with the solution you built. Sometimes the best AI lesson is a business lesson first. Kim Bennett of AtlasGuru Data Strategy Comes Before AI Strategy Another critical lesson: AI is only as good as the data behind it. You can’t build an AI strategy on top of messy data. If your data isn’t clean, centralized, and standardized, AI will just amplify the chaos. Stephanie Smith In hospitality, data is often spread across dozens of systems. Before organizations run with AI, they need to walk through the foundational work of data governance, consistent metrics, and standardized processes and documentation. AI without context is just autocomplete. The organizations getting real value are the ones feeding AI with information no one else has. Saadiq Rodgers-King Guardrails Matter (Especially with MCPs) AI integrations like Model Context Protocol (MCP) can connect AI to real business systems. But with that power comes responsibility. Just because AI can take action doesn’t mean it should. The smartest implementations define clear boundaries between what AI suggests and what humans approve. Stephanie Smith Thoughtful permissions and review processes are essential as organizations begin connecting AI to operational systems. We’re moving from AI that can answer questions to AI that can take actions. MCP lets AI connect to your actual business systems. That’s incredibly powerful, but it also means you need to be intentional about what you let it do versus what still needs a human