Technology

The AI platforms need to monetize their traffic, since AI computing is exceptionally expensive! The quickest way to do so is to partner with well-established travel brands and to start earning affiliate commissions from them. To achieve that, AI connectors play a crucial role, but what kind of connectors?The keyword here is “invisible B2B connectors” that service well established hotel and travel brands, but remain invisible in the background.Ex.

The question lands precisely where the industry tends to look away. Travellers do not wake up wanting orchestration. They want outcomes: the right option, at the right price, with minimal friction and maximum trust. The moment a connector introduces one extra decision — which system to link, whether it is safe, whether it will work — adoption collapses outside a narrow power-user segment.Where connectors genuinely solve a problem is on the supply and enterprise side.

At least in their current form, I think AI connectors risk solving more of an industry problem than a real user need.The idea of a unified journey makes sense, but it breaks when it assumes that travelers will actively connect tools, authorize systems, and manage infrastructure they’re not familiar with.

Specific to the thrust of Max's question, in this context we are referring to search/find from the booking/transaction perspective. In that light...For me it is the next generation of search.Depending upon the user, we can now be far more specific with the input to get more targeted output.We will be able to speak and converse, which is more natural and a next gen over multiple queries or filters.I do believe that when the buying time comes after the research phase the customer will still 'come' to the point of booking.

The Internet enabled you to find things yourself. Agentic AI will do everything for you. That’s why it’s: Much bigger than blockchain or the metaverse. And closer to how big the Internet was.

“When your grandmother can use a new technology, that’s when you know it will reach widespread adoption.” I’m paraphrasing this Kevin O’Leary here but the principle is nevertheless highly instructive for why blockchain and metaverse technologies didn’t have prominent adoption in the travel sector.

Guest preferences for automation vary significantly by region. Business heavy markets in Europe and North America lean toward automation, while the Gulf and Far East tend to favor human interaction, partly driven by lower trust in technology.Regardless of hotel tier, certain roles will always remain in human hands, e.g., chefs, spa therapists, maintenance engineers, duty managers, and any function centred on safety, emotional intelligence, or complex judgment.

Replace - very junior level "support" roles who mainly answer "how do I do this" type of questions. AI agents will be trained on SOPs and do this. Help desk staff can be reduced or upskilled for more complex work.Reshape - Contact Center Agents: As above, simple questions can be answered by AI Agents, and an AI powered PBX will answer the phone for high volume restaurants and make the bookings on a phone call via integration to table booking system, and send confirmation by SMS or WhatsApp.

AI won’t replace hospitality, but it will reduce the number of people needed to run it.In the next 3 years, we’ll see 30–60% productivity gains across call centers, guest messaging, revenue management, distribution, loyalty, back office, and even parts of development.This is not just automation, it’s a redefinition of roles.

OpenAI just admitted what Google already learned with "Book on Google" back in 2022: people use AI to discover, not to buy. I fully agree with Simone the reason is structural, not technical. A hotel booking is not a single transaction.

Conversational platforms will complete bookings, but not by simplifying hospitality's complexity. They will succeed when they can orchestrate it. Today a single reservation touches PMS, CRS, channel management, payment processing, cancellation logic etc.

I’d agree. A retail transaction, even a high value one, is much simpler than a hotel or flight booking. Shopify is a top retail IBE, but its funnel is much simpler (view products, select product, pick colour, select size SMLXL, add to basket, add an upsell box of chocs, set delivery address, etc), than the well-converting IBEs in hospitality like Journey, Net Affinity, P3, Profit Room, Allora etc.

Optimising AI literacy in F&B operations starts with a simple principle: buying technology is not the same as building capability.Too many operators still approach AI as a procurement exercise rather than an operational transformation discipline.

AI investments in F&B deliver value only when adoption is treated as seriously as the technology. The implementation gap is rarely caused by weak tools. It is usually caused by weak translation between strategy, tech implementation and frontline execution.

AI literacy in F&B does not start with tools. It starts with understanding what the operation actually produces.Most teams I see try to adopt AI before they can even describe what their workflow does step by step – mostly for the lack of SOP.

In a word, no. Websites were designed to entice humans to view, discover, consider, buy. They are heavy with images, HTML, JavaScript, etc. to entice us in and encourage us to dwell. APIs were invented for M2M, machine to machine, transactions.

Agents will be everywhere, but behind the scenes. Booking agents are a short-term solution; using AI to simulate human behavior is like asking for a faster horse. Agents that behave as people, visiting websites and simulating human behavior (clicking on links, filling forms) are an incredible technological feat, but are a poor solution to most real-word problems: - Agents are very slow, because they have to replicate user paths built for humans- They fail often, because every website they visit is differentThe future will be MCP- and API-based, with agents interacting with those MCP/API.

Crystal ball time. 5 to 10 years i think we will quite similar to where we are today. the slow pace of change will not change and traditional tech stacks will still be around. lack of motivation to change, contracts and low investment will hinder the change.

Hotels are better positioned for the AI era than most people think. They own something no LLM can replicate: years of proprietary guest data and a direct relationship with the customer. That's a genuine competitive moat, and agentic AI is finally what turns it into action.

The takeaway that stays with me isn't about any single technology. It's about what AI can actually do to change the way we experience travel.An example of this was the live demo I gave on stage to change my own flight home - not by calling a helpdesk, not by navigating an app - but by having a natural conversation with an AI agent that handled everything live: rebooking, seat, baggage, transfer all in one simple phone call.The audience went quiet for a moment.

What stood out to me most at ITB Berlin this year was how much the conversation around AI has shifted from theory to real, everyday use. Hoteliers and operators are no longer asking whether AI matters, but where it can make the biggest difference for guests and teams right now.

The most transformative disruption we’ll bring to the hospitality industry by 2026 lies in end-to-end workflow automation across hotel operations, not just individual tasks, but entire processes that currently require too much manual effort with too many handoffs and that may unnecessarily create security risks in today's high data security environment.

We believe AI will most profoundly disrupt operational scheduling and resource allocation across spa, wellness, and leisure departments. These areas are traditionally managed through manual guesswork, disconnected systems, or static templates.

I believe the biggest disruption isn’t a single task - it’s the entire commercial workflow behind meetings and group bookings. A third of all hotel room nights tie back to a meeting or group, yet hotels still burn thousands of hours on manual qualification, data gathering, and proposal-building.

It's abundantly clear that the US hyperscalers are unable and unwilling to regulate themselves. A $100 million pro-AI super PAC formed in August, backed by OpenAI's president, has identified its first pro-legislation target to oust.

The divergence in AI regulation is less about "innovation versus control" and more about who will define the operating system of the future economy. The US optimises for velocity and scale; the EU for rights, accountability, and systemic risk.

Yes, the gap in AI innovation and adoption will continue and expand. This disparity is less about well-intentioned policy and more about an ongoing geopolitical battlefield where technology sits squarely in the 'armed forces' of the major powers.

In my previous airline and telcoms world, we used service buses like TIBCO to sit on top of enterprise systems. The upside was the potential of plug and play (although we never actually changed back end ERPs). The downside was extra latency and cost.

The integration hub solution is different for every hotel. The easiest answer starts with new brands or independents. Heading into 2026, there are several great PMS and GEMS players that can fulfill a variety of central operations so that one-off integrations amongst disparate, single-use services aren't as necessary as they were a few years ago.

In practice, it's not that simple. A hub always depends on common integration standards — yet many systems still lack proper REST APIs to communicate effectively. For example, we dynamically manage room assignments and reassignments based on guest fit and preferences, but not all PMSs even offer APIs that allow us to do this.

The problem isn't that personalization fails on property. The problem starts much earlier: we still don't speak the right language of guest experience in the digital space. Take booking. A traveler may want a big bed, a walk-in shower, and a quiet location.

Online personalisation is easy, as it's mostly a pattern-matching algorithm between known guest preferences and available services. It isn't personalisation, rather just mass customisation. On property, a guest walking around is essentially anonymous, even after checking in.

This is a question at the heart of hospitality’s digital transformation. Hotels excel at digital personalisation (curated offers, smooth booking, and tailored communications) because online, data is structured, accessible, and actionable.

When it comes to where our Distribution landscape is headed - it's not even a question. Of course uniting our efforts is the only way to go. Otherwise we'll lose another OTA battle. But there's much more to the world of AI functionalities, it has its tenticles in every part of our tech ecosystem, not distribution alone.

I think we are in danger of running before we can walk here. MCP is Anthropic’s pitch for an open standard to let "agentic AI" bots built on next-word LLMs share data, for example, an OpenAI bot talking to a Gemini bot. Unless you are Marriott or Hilton with hundreds of in-house developers, or a big OTA like Expedia or Booking.com, this really isn’t something you need to worry about.

You could establish your own protocols instead of MCP, A2A, or other widely endorsed standards for agentic interactions. But that would be like creating your own version of HTTP. Not a great idea. The good news is I don't think companies feel the need to change that basic agent-friendly plumbing.

Everyone wants the hotel tech stack to be more guest-centric and hopes AI will help to deliver a more personalized experience. This future will be centered around the PMS as the hub for rooms-centric operations and the CRM/CDP for repeat-visit-oriented relationships with guests.A strong connection between these two systems is vital to have the CRM/CDP ingest the most information about guests so that ML has big and accurate data sets by which to recommend segments, retool rates, create suggested packages, A/B upselling offers and so on.But both of these systems are back-of-house.

There is really no difference between preparing data for Gen AI and for other tech tools: structured data must be normalised, deduplicated, and governed, while Gen AI is best applied to unstructured sources like reviews, transcripts, or free-text notes.

AI in hospitality cannot be reduced to a fixed list of use cases, because the technology and its applications evolve too quickly and vary too widely across companies. Each organisation runs on its own mix of operations, tech stacks, data flows, and structures, which means their AI opportunities will always be unique to their context and business challenges.

The age of the hotel brand is ending. For decades, franchises have scaled by selling sameness, consistency over individuality. AI breaks that logic. AI reshapes the vectors of discovery. Instead of guests defaulting to familiar logos or loyalty programs, intelligent systems surface the properties that best match a traveler's needs, preferences, and context.

This is part of a bigger question, I think. As a marketing guy, let me explain it through distribution, using Booking.com as the example. Booking spends billions on advertising, dominates search, builds the user experience that has become the industry template, and runs a multilingual customer service that often outperforms independent hotels.

Yes. It's not limited to franchises and is a pretty long standing clause in agreements. There largely because it was not as prominent a consideration back in the day from a data and technology perspective - harder to get data out of a peice of on premise technology that the owner paid for.

About 18 months ago, some people on LinkedIn touted that Conversational Interfaces would kill off websites. Current status? Tumbleweed. Visuals sell things, text supports. Websites enable owners to portray their brand and products/services as they see fit.

The rapid advancement of AI, especially agentic technologies, is fundamentally changing hotel distribution and guest engagement. Recent data shows that only about 25% of AI-generated hotel information now comes from hotel websites; the rest is sourced from OTAs, public databases, and proprietary data.

I don't believe AI will make hotel websites obsolete. If we learn anything from the past, every obstacle creates opportunity. Technology's direction isn't a single script; there are multiple paths and approaches. Where a problem needs to be solved, a tool will emerge to solve it.

What's always amazed me is the lack of real-time coordination between the hotel and dining teams in terms of already knowing guest preferences the moment they identify themselves at the restaurant host station. Precisely because there isn't typically quick coordination between these two silos, that leaves a ton of room for wow moments that technology can execute in an automated, scalable and real-time manner.

Seamless Data: The Truth About Why Your Organization Isn't There Yet In the dynamic landscape of hospitality, the growing momentum towards unified hotel technology and seamless data flow across departments and guest touchpoints is undeniable.

The idea of crafting experiences around a centralized, real-time guest profile represents more than a technical upgrade; it signals a paradigm shift. We are moving from an analog conception of hospitality to a computational one, where data no longer serves the experience but is the experience.

Our work with clients on personalization is rooted in the fundamental view that we've always aimed to better match what we have to offer with what a guest truly desires. This is particularly crucial when a property offers a diverse range of products beyond just rooms, where strategic personalization can genuinely elevate the guest's enjoyment by more accurately aligning offerings with their individual preferences.

The real threat today isn't personalization creating an echo chamber, it's hotels failing to meet the expectations of generations raised on TikTok, Spotify, and Instagram. Gen Alpha and Gen Z aren't marveling at algorithmic recommendations; they expect them.

Let's be blunt: most hotels haven't even reached personalization, let alone hyperpersonalization. And while Booking.com, Netflix, and Amazon are masters of knowing what you want before you do, many hotels still worship the PMS like it's the digital holy grail.