Innovation

Bangkok, Thailand, August 24, 2026 – Shiji, the global leader in hospitality technology, today announced that Wyndham Garden Phuket Kamala has successfully deployed Infrasys POS , Shiji’s cloud-based point-of-sale platform. The implementation supports the resort’s operational requirements across its food and beverage venues, enabling more connected service workflows while maintaining a consistent, guest-focused experience. Located on Kamala Beach in Phuket, Wyndham Garden Phuket Kamala operates multiple dining outlets alongside poolside service, in-room dining, and event spaces. To support this operational environment, the resort selected Infrasys POS to unify food and beverage operations across service points while ensuring ease of use for staff and consistency in guest interactions. Designed for cloud-first hospitality environments, Infrasys POS enables real-time transaction processing, centralized menu and pricing management, and integration with wider hotel systems. These capabilities allow service teams to operate with greater mobility and visibility, reducing manual processes and supporting faster service during both peak and seasonal demand periods. “Infrasys POS is designed to support hospitality operations where service is delivered across multiple venues and guest touchpoints,” said James Liaw, General Manager for Singapore and Thailand of Shiji Group. “By deploying a cloud-based POS platform, Wyndham Garden Phuket Kamala has established a flexible operational foundation that supports efficient service delivery while remaining adaptable to future needs.” Through the implementation, Wyndham Garden Phuket Kamala gains centralized control over menus and pricing, improved operational insight, and the ability to manage seasonal menu changes and high-volume service periods. These capabilities are particularly relevant in Phuket, where guest demand fluctuates throughout the year and service teams must respond quickly to changing volumes. “We required a POS system that could support seamless food and beverage service across the resort without adding complexity for our teams,” said James Yang, Assistant Hotel Manager of Wyndham Garden Phuket Kamala. “With Infrasys POS, we are able to operate more efficiently across outlets while continuing to deliver the level of service our guests expect.” The deployment at Wyndham Garden Phuket Kamala reflects a broader shift among resort and upscale hospitality operators in Southeast Asia toward cloud-native technology platforms that support connected operations and real-time decision-making. As hotels continue to modernize their technology ecosystems, POS systems such as Infrasys play a key role in linking food and beverage operations with the wider guest journey. About Wyndham Garden Phuket Kamala Wyndham Garden Phuket Kamala is a contemporary beachfront resort located along the tranquil shores of Kamala Beach, offering guests a relaxed tropical escape with modern comforts, curated dining experiences, and a focus on approachable luxury. Designed for both leisure travelers and families, the resort blends international hospitality standards with the natural beauty and cultural richness of Phuket.

A few weeks ago I was on an intake call with a potential coaching client. She is a Director of Rooms at a luxury property in the far east, mid-thirties, sharp and hungry for her next move. Director of Operations, maybe a GM seat down the road. Like every intake call, I asked my standard opening question: how did you find me? Her answer stopped me cold. She asked ChatGPT. Not "who is David Lund" – she had never heard of me. She asked something more like, "I’m a Director of Rooms at a luxury hotel and I want to grow my career, but I’m weak on the financial side. Who can help me?" And the machine gave her my name. Some of you may remember my story about being recognized in a castle hotel in Portugal – my 15 seconds of fame, courtesy of a General Manager named Carlos who reads my weekly blog. That was fun, but this is different, and I think much more important. Carlos already knew me. This lady did not. A machine introduced us. So I did some digging into how this actually works, because if it happened to me, it can happen to you, and I think every hospitality professional should understand it. The brochure rack and the concierge Think about the difference between Google and AI the way you would think about two fixtures in any hotel lobby. Google is the brochure rack. You walk up, you flip through, and it hands you ten options ranked by whoever played the ranking game best. You still have to sort through them yourself. AI is the concierge. You do not ask the concierge for a list. You tell the concierge your problem – "I need a quiet dinner spot where I can actually talk business" – and a good concierge gives you a name. "Call Maria at the little place on the corner. Tell her I sent you." One answer, matched to your problem. Here is the part most people get wrong. These AI systems do not keep a list of approved experts. Nobody registered me. Nobody paid a fee – you cannot, at least not yet. What the machine did was read. It read an almost unimaginable amount of the internet before anyone ever typed a question into it. And somewhere in all that reading, one association got made over and over: this name, this subject. A weekly blog, a book, articles in the industry press, a LinkedIn feed – all saying the same thing, year after year. The machine learned to connect a name with a problem the same way you learned that a high labor cost flows straight through to the bottom line. It saw it enough times that the connection stuck. Google asks: which webpage should I show first? AI asks a very different question: who or what is most associated with solving this problem? Those are two different games, and the second one heavily rewards specialists. Ask "who is

Cast: Rajeev Ratti, Niale McLoughlin, and me — Terence Ronson. Mission: fill the hotel, keep the guests happy, and — most days — stay sane. When we first arrived, we were not exactly overqualified for the role. None of us spoke a word of Cantonese. Niale had no previous Front Office experience, having mostly worked in restaurants. My own background was as a trained chef, though I'd been fortunate enough to pick up a couple of years of Front of House experience before wading into this enormous bed factory. My own background was as a trained chef, though I'd been fortunate enough to pick up a couple of years of Front of House experience before wading into this enormous bed factory. Terence Ronson RAJEEV: I'd just graduated from the Institute of Hotel Management in New Delhi when Hong Kong came calling. A few months later, I joined Terence and Niale as a fellow Lobby Boy — officially, Assistant Manager — and never looked back. Terence and I share a birthday, a year apart, which we always felt made the arrangement official — the Three Musketeers, one for all and all for one, minus the swords. Read the full story of The Lobby Boys. Available now. By Terence Ronson, on behalf of The Lobby Boys — Niale, Rajeev, and Terence

📱 ChatGPT serves ads on 47.7% of all prompts, while Google does so on 25.5%. These statistics were mentioned by Writesonic, although the calculation method is unclear. There is interest in exploring differing estimates or thoughts on these figures from LinkedIn colleagues, considering variables like model specifics, ad definitions, and platform differences.

The week closes with three pieces that each take the AI infrastructure argument somewhere concrete. Lighthouse puts a real-time scoring engine on hotel website visitors, moving AI from discovery to conversion at the property level. Pertlink documents what it looks like when a destination builds the data layer before the interface, which is the opposite of how most hotels are approaching the problem. And The Sales Leadership Brief makes a commercial capability argument that has nothing to do with AI but everything to do with what the industry will need when the current demand cycle normalises. AI Can Already Tell You Which Visitor Is About to Book and Which Is About to Leave Lighthouse Direct's explainer on its AI visitor scoring system describes five algorithms running simultaneously on hotel website visitors: intent scoring, spend propensity, destination flexibility, date flexibility, and length-of-stay prediction. The system identifies high-intent, rate-sensitive visitors in real time and serves targeted offers calibrated to protect ADR rather than discount indiscriminately, with conversion lift measured against control groups across the properties running the product. The piece closes this week's AI content loop precisely. Monday established the content restructuring required to appear in AI discovery. Tuesday and Wednesday covered the optimization layers for AI agents. This piece reaches the conversion end of the same funnel: once a visitor lands on the hotel website, AI is already available to decide what to show them and when. The gap between hotels using it and those not is already measurable. Read the explainer → The Terminal Is the New Homepage Pertlink documents Shanghai's network of 100 AI-powered tourist information terminals, built on a unified data layer of 84,000-plus content entries and 14,000 booking links before any interface was designed. The piece presents it as a reference model for destinations, and for hotels, on the correct sequencing of AI infrastructure investment: build the structured, machine-readable data layer first, then build interfaces on top of it. Most hotels and most destinations are doing this in reverse: launching AI interfaces on top of fragmented, incomplete, unstructured content that the interface cannot use effectively. The argument connects directly to IHG's Kim Smith interview on Wednesday. Her most actionable recommendation was to restructure property descriptions around use cases before deploying any AI tool. Shanghai's terminal network is what that recommendation looks like at destination scale, built systematically rather than retrofitted. Read the analysis → What Emerging Markets Taught Me About Hotel Sales That Luxury Markets Never Could The Sales Leadership Brief's hotel sales veteran argues that emerging market postings build commercial instincts that luxury markets structurally cannot: demand creation in the absence of inbound flow, relationship-led selling before RFP cycles exist, and pricing discipline under conditions where there is no comp set to hide behind. The piece frames emerging market sales experience as the most rigorous commercial training available in the industry, and argues that luxury hotel sales, which primarily harvests existing demand at high rates, produces strong revenue results but weaker commercial capability. The argument directly

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