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.