Technology in Hospitality

I think a very visible observation at this year's Restaurant Show was logical tech instead of theoretical. There was less "glimpses into the future" and more "proof of concept." Here's one of those in action: For two and a half years, Wingstop has worked on a new Smart Kitchen that forecasts demand in 15-minute increments, telling the store how many wings to drop. The system takes into account more than 300 variables tailored to each unit, like weather, sales trends, and sports. It also features digital touch-screen displays at every work station instead of paper chits and an order-ready screen at the front so consumers can keep up with their order. Another feature: there are now sticker print outs that identify what flavors are in each package. At restaurants where the technology has been installed, wait times have been cut in half to about 10 minutes, and there have been notable improvements in guest satisfaction, accuracy, consistency, and employee turnover. In the delivery channel, Wingstop has been able to show up in under 30 minutes. Why is this important? Shorter wait times allow the brand to become a greater consideration. Instead of serving as a destination—with an average frequency of just three times per quarter and once a month—the quicker service could entice guests to visit more often, especially during on-the-go periods like the afternoon daypart. The Wingstop Smart Kitchen is in 400 restaurants and the chain hopes to complete the rollout by the end of the year. Again, real-time innovation in the back of the house. That seems to be the battleground right now. More here: https://lnkd.in/eMHMUkmZ

Nestlé bets on generative ai – not for efficiency, but for growth Nestlé, the world’s largest food and beverage company with 2,000+ brands in 185 countries and a Fortune Global 500 rank at No. 97, is reshaping its operations with AI - not just to cut costs, but to drive strategic value and growth. Under CIO Christopher Wright, Nestlé is deploying generative AI across the value chain: from automated fulfillment planning and dynamic pricing analytics to enhanced sales support workflows. Smaller retailers now receive AI‑generated order plans that improve accuracy and drive higher conversion. A global SAP S/4HANA backbone and centralized data foundation enable scalable AI pilots - Microsoft Copilot is used by ~100,000 workers monthly. Nestlé is also applying AI for transport auctions, factory maintenance planning, and virtual sales assistants. While Nestlé plans to reduce ~16,000 white‑collar roles, Wright underscores that AI’s role is to reallocate time toward higher‑value activities, not simply eliminate jobs. Why it matters: In a complex, low‑margin industry, Nestlé’s example shows how AI can unlock end‑to‑end value - improving demand forecasting, pricing, execution and customer engagement simultaneously. AI becomes a strategic force multiplier rather than just a cost lever. What other FMCG giants are doing: • Unilever uses AI in its ice cream supply chain spanning ~60 countries and ~3 million freezer cabinets; AI‑enabled forecasting improved accuracy by ~10% in Sweden, and sales rose 8–30% in pilot markets. Unilever has implemented 500+ AI‑based capabilities globally and integrates AI from planning to execution. • Mondelēz International (Oreo, Cadbury, Chips Ahoy) invested > $40 million in a generative AI marketing tool to cut content production costs by 30–50%, with plans to generate AI‑based TV ads by the 2026 holiday season. • Procter & Gamble (P&G) is harnessing AI to accelerate ad optimization cycles from weeks to days and deliver up to a 90% reduction in related costs through AI‑powered media testing and analytics. These moves illustrate that major FMCG players are scaling AI for forecasting, supply chain agility, content production and marketing optimization—not only to improve efficiency but to strengthen competitive differentiation and growth. #retail #fmcg #ecommerce #sales #marketing #ai #generativeai #digitaltransformation #sap #microsoftcopilot #automation #futureofwork #supplychain #datadriven #pricingstrategy #virtualassistant #omnichannel #foodtech #retaitech #globalexpansion #innovation #efficiency #growthstrategy #leadership #cio #switzerland #europe #usa #india #philippines #brazil #northamerica #asia #unilever #mondelez #pg

Chipotle just gave the POS market a very loud signal. They signed a six-year exclusive deal with NCR Voyix, and they’re the first to roll out NCR’s next-generation Aloha POS, built on the Voyix Commerce Platform with a dual-cloud, edge-enabled microservices architecture. That combination matters more than it sounds. For years, “cloud POS” often meant: move the same old POS to a different place. What Chipotle is implementing is closer to what modern retail tech should look like: software that can evolve fast, ship updates safely, and keep running even when the network is having a bad day. And a bit of context makes this even more interesting. Aloha is not a new player. It’s one of the most established restaurant POS platforms, originally built outside NCR, acquired by Aloha Technologies long ago, then folded into Radiant Systems. Radiant was later acquired by NCR in 2011, which is how Aloha became a core part of NCR’s restaurant stack. Fast forward: NCR rebranded to NCR Voyix after its separation plan, and the company has been building toward end-to-end commerce (restaurants + retail), adding pieces like payments (JetPay) and local restaurant market reach/support (Foremost Business Systems). So what’s the real takeaway for POS vendors and retailers? This isn’t “the POS is dead.” It’s the opposite: the POS becomes the stable transaction engine, while a modern platform around it makes everything faster to change: pricing logic, loyalty, digital ordering, kitchen orchestration, fraud signals, personalized ops prompts… without turning every release into a risky big-bang rollout. Chipotle is basically saying: this architecture is now enterprise-grade. If you build POS software (or depend on it), the question for 2026 isn’t “cloud or on-prem?” It’s: how quickly can your POS evolve without breaking compliance, uptime, and operational discipline? Curious: do you think the next competitive edge in restaurant tech will come from the POS itself or from the platform that surrounds it? #retail #innovation #pointofsale

All retention strategies are not created equal. Or are they? In 2025, companies compete on belonging, not benefits. In the old days, pizza parties and ping pong tables worked. Now you need systematic approaches to keeping talent. Here's 4 levels of employee retention you must understand: LEVEL 1: REACTIVE - PEOPLE QUIT → WE ASK WHY AFTER This is retention theater. Exit interviews where people lie about "new opportunities." Desperate counteroffers that never work. Managers shocked when their best performer gives notice. What it looks like: - Exit interviews only - Last-minute counteroffers - High regret turnover Your HR team is a coroner doing autopsies, not a doctor preventing disease. The fix: Start with stay interviews. Ask people why they stay, what would make them leave, what energizes them. Do this quarterly. Act on what you learn before they're halfway out the door. LEVEL 2: PROGRAMMATIC - ONE-SIZE-FITS-ALL PERKS Pizza Fridays. Wellness days. Ping pong tables. The same tired benefits whether you're 22 or 52, single or supporting a family, engineer or accountant. What it looks like: - Wellness days, swag, offsites - "Engagement" via pizza - Culture defined by events You're throwing spaghetti at the wall hoping something sticks. Spoiler: it doesn't. The fix: Tailor benefits to real needs. Survey by team AND tenure. New parents need different things than empty nesters. Engineers value different perks than salespeople. Stop guessing, start asking. LEVEL 3: STRATEGIC - RETENTION DESIGNED INTO SYSTEMS Now we're getting somewhere. Career paths are clear. Promotions happen on schedule. High-potentials know they're valued. Every process reinforces that growth happens here. What it looks like: - Growth tracks by function - Skills-based promotions - Embedded feedback loops You're not reacting to turnover. You're preventing it through structure. The fix: Align L&D with succession planning. Track mobility rates quarterly. Make internal moves easier than external ones. If someone has to leave to level up, you've already failed. LEVEL 4: CULTURAL - PEOPLE STAY BECAUSE THEY BELONG The holy grail. People stay because leaving would mean losing something irreplaceable. Not perks or pay - belonging. Purpose. The feeling that their work matters and they matter. What it looks like: - Psychological safety - Purpose-driven work - Peer recognition culture Your culture is so strong that recruiters can't poach your people with 30% raises. They've tried. The fix: Train every manager on trust-building. Not a workshop - ongoing coaching. Reward inclusive leadership as much as hitting numbers. Make belonging a metric, not a buzzword. TAKEAWAY: The companies winning the talent war understand that people don't leave companies. They leave cultures that don't value them. They leave managers who don't develop them. They leave futures they can't see. Fix those three things, and retention takes care of itself.

I mapped 120+ hotel tech companies across 14 categories onto a single page. Here's the full 2026 hotel tech stack, organised the way it actually works. Most hotels run a dozen tools and have never seen them laid out together. So I built the map. Every category, the credible players in each, in the order a hotel actually adopts them. Here's how it breaks down: 1. The core: Your PMS sits at the centre, everything else plugs into it. Get this right first, because every other decision depends on it. Examples include: Mews, Cloudbeds, Oracle Hospitality, Apaleo, Stayntouch 2. The revenue layer: -> Revenue management: is the brain. It tells you what price to charge for each room, on each night, based on demand signals, competitor rates, booking pace, and historical data Examples include: IDeaS Revenue Solutions, Duetto, RoomPriceGenie -> Channel management: is the distributor. It takes that rate and pushes it out to all the places where rooms are sold: Examples include: SiteMinder, D-EDGE Hospitality Solutions -> And your booking engine captures the guests who come direct, without paying OTA commission. Examples include: The Hotels Network, Triptease, Profitroom. 3. The guest layer: Everything the guest actually touches. Messaging and guest experience: Examples include: Canary Technologies, Duve, Bookboost, Asksuite Reputation Management: Examples include: TrustYou,Shiji Reviewpro Reputation GuestRevu 4. The operations layer:i ncl The tools your team lives in but guests never see. Housekeeping and staff ops, payments, business intelligence, smart room and access. Examples include: Unifocus, hotelkit, Alice by Actabl, Flexkeeping. Business intelligence: the layer that tells you how the whole operation is actually performing. Examples include: Lighthouse, Actabl, Juyo Analytics, M3 (Full map below. Save it for your next stack review.) P.S. Which ones would you add?

🚨 New Elevation Capital thesis: Quick Commerce x Food! Indians today have come to instinctively check Instamart or Blinkit before Amazon for daily needs. Capitalising on this shift, quick commerce has expanded from a few thousand SKUs to 20,000+ in dark stores, with megapods offering 50,000 SKUs across multiple categories including apparel, electronics, and long-tail items. Despite horizontal expansion, 80% of GMV for quick commerce companies remains grocery-driven, leaving significant room for vertical specialization in other categories. These new vertical quick commerce models are bridging the offline-online experience gap, where quick is one axis of innovation, not the sole focus. One such vertical is food. It's creating new consumption by capturing offline and packaged food consumption rather than cannibalizing existing delivery. For instance, Swish has been at the forefront of innovation in selecting demand occasions and building consumer habits in this space. Some highlights: > Hot beverages unlock entirely new demand - traditional 30+ minute delivery made ordering coffee/tea impractical due to temperature and taste degradation > Quick food platforms reduce cognitive load by curating options vs. endless restaurant scrolling on traditional food delivery apps > Snacking and beverages drive initial adoption, creating opportunity to expand into main meals > Full-stack approach required - companies must control sourcing, cooking, technology, and logistics end-to-end > Food prep technologies include deep frozen, cook-and-chill, and fresh preparation > Current models primarily use partially prepared bases with final cooking steps completed at point of dispatch - similar to QSR > Key challenges: variety expansion beyond core dishes, price competitiveness and solving for trust/perception gap > Main meals (lunch/dinner) emerging for low-cognitive decision occasions like rice bowls or salads where brand matters less than quick, fresh delivery

Dubai Approves City-Wide Digital Hotel Check-In A major leap in integrating digital identity, tourism, and smart-city infrastructure. Dubai has adopted Digital Hotel Check-In as a primary channel across all hotels and holiday homes. A national digital infrastructure shift connecting identity, travel, security, and tourism into one seamless ecosystem. 1. Dubai’s Tourism Scale — Why It Matters Dubai operates one of the world’s largest tourism systems, requiring infrastructure-level solutions rather than hospitality fixes. Key Figures: • 17.15M visitors (2023) • 18.72M visitors (2024) • 9.88M visitors (H1 2025) • #4 globally for international tourism • 825+ hotels ~151,000 rooms • 77–83% occupancy • ~AED 150B tourism contribution to Dubai • ~AED 236B UAE-wide (12% of GDP) • 92M+ passengers at DXB (2024) On peak days, 50,000–70,000 tourists arrive. Manual reception check-ins = bottlenecks. Digital identity check-in = infrastructure. 2. What Digital Check-In Delivers • Biometric verification via UAE Pass • Under 1-minute digital registration • Encrypted, secure data storage • Unified city-wide standard across all hotels 3. Global Benchmarking — Dubai Pulls Ahead Global reality: • USA: 30–35% partial digital check-in • EU: no unified digital ID standard • Asia: fragmented adoption • Worldwide: only ~22% biometric check-in Dubai’s lead: • 100% digital identity integration • Mandatory adoption across all hotels • Government-verified identity • Unified compliance • Smart-city scalability Dubai is years ahead of global tourism hubs. 4. Hotel Impact — Efficiency at Scale Operational gains: • 30–40% fewer queues • 25–35% less manual verification • 20–30% lower check-in costs • Fewer identity errors Performance gains: • Higher satisfaction • Faster room turnover • Better forecasting Across 825+ hotels, this unlocks: → Millions in annual savings → Thousands of staff hours freed 5. Part of the UAE’s Digital Architecture Foundations: • 99.5% of Dubai government services digital • 11M+ UAE Pass users • Digital economy target: 19–20% of GDP by 2031 • UAE ranks #1 regionally in digital competitiveness Digital check-in now fits into a unified national flow: Identity → Travel → Tourism → Security → Payments → Government Services 6. The Future: AI-Driven Tourism Intelligence Digital check-in unlocks: • AI prediction of visitor flows • Dynamic hotel staffing • Smart mobility routing • Personalized city-wide visitor journeys • Stronger national data sovereignty Dubai Is Not Digitizing Hotels. It Is Digitizing Tourism. Tourism is no longer a service — it is a digital system. Dubai is redesigning the entire arrival experience where: • Identity is seamless • Hospitality is instant • Data is secure • Operations are efficient • Growth is scalable • AI is inevitable While the world discusses the future of tourism, Dubai is enacting it at infrastructure scale.

Boom is a two-year-old AI-powered hospitality management platform whose latest funding round is a shot across the bow for every CXM platform with a foot in hospitality. The Bay Area-based company just raised $12.7 million to weave AI into the operational fabric of hotels. If you recall, Medallia started with Hilton as its first customer, so this is a particularly interesting story to follow. Boom isn't offering a chatbot in the lobby. On the contrary, they're promising conversational AI, hyper‑personalization, and predictive analytics that can learn, adapt, and autonomously manage complex tasks. Why does this matter for Qualtrics, Medallia, Sprinklr, and every other CXM vendor with hospitality clients? Because the data plumbing and decision‑making layers are moving deeper into the hotel. They're not going to live on a dashboard or inside a GenAI capability that a hotel manager uses to automatically generate a response to a low-NPS guest. This stuff will go by the way of the dodo bird. Imagine what this could look like: At Hilton, their Watson‑powered concierge “Connie” (now nearly 10 years old) answers questions about amenities and local restaurants. With Boom's AI capability, Connie could remember your running route from your last stay, pre-book your gym slot, and push a personalized offer through your loyalty app before you even unpack. Marriott Hotels has tested in‑room voice assistants that let guests control lighting and temperature. Layer predictive analytics on top, and the system could anticipate when you typically request room service, ask if you’d like your favorite snack delivered, and feed that behavior back into Qualtrics or Medallia for real‑time NPS tracking if you're into that sort of thing. Here’s how hospitality brands can turn this technology into magic: Connect your feedback loop. Integrate AI‑driven interactions with your CXM platform so every guest preference and sentiment automatically informs product and service tweaks. Train employees to be AI translators. Your staff should know how to interpret AI signals and add the human touch, whether it’s a concierge upselling a spa package or a manager smoothing out a glitch. Pilot, then scale. Start with a single property or service (e.g., check‑in) and use tiger teams to refine the experience before rolling it out chain‑wide. Frankly, I think Boom is ripe for a CXM provider looking for a nice tuck-in acquisition to boost their action-focused future and valuation. Because the future is not about delivering thermometers. The future is about enabling action at scale. Boom’s vision hints at a future where hotel stays feel bespoke at scale. If you were running Hilton or Marriott’s CX program, what’s one AI‑driven experience you’d implement tomorrow? #customerexperience #hospitality #ai #futureofwork #cxm #saas

How did an iconic hotel in Singapore, Marina Bay Sands, cut labor dependency with AI and robots by 30% while simultaneously generating 162,000 manhours of greater value with its staff? The secret lies in treating AI and robotics as a partner for your people, not a replacement. Marina Bay Sands (known as MBS here) in Singapore, a large-scale integrated hotel + casino + mall, is demonstrating that AI and robotics are now fully viable for complex, large-scale hospitality operations. MBS became the first in Singapore’s hospitality industry to deploy a fleet of 12 Autonomous Mobile Robots (AMRs) for back-of-house deliveries across its hotel and convention center. Facing a 35 percent surge in delivery volumes between 2019 and 2023, the resort turned to automation to manage growing demands. The deployment of AMRs, which handle manpower-heavy tasks, carrying up to 300kg and moving at 84 meters per minute, resulted in a 30 percent drop in labor dependency. However, the crucial insight for long-term value and staff adoption is the strategic focus on the workforce, repurposing Talent for Sustainable Value. MBS's comprehensive automation efforts, which include over 200 automated work processes across various functions (like 'The Wardrobe' system managing over 200,000 uniforms via ultra-high-frequency chips and automated stocktaking, or the automated upcycling of 100% of food waste by end of 2025), have resulted in the repurposing of over 162,000 manhours annually towards greater value-added tasks. For example, instead of job elimination, members of the procurement and supply chain teams who previously handled manual deliveries are now trained in new, higher-value roles such as inventory management and robot dispatching. By investing in innovation and fostering a culture of productivity, MBS leadership proves that successful integration requires to be people-driven just as much as you are AI-driven. Repurposing staff generates motivation, long-term value, and ensures technology adoption, making automation a key driver of human capital enhancement. full article here: https://lnkd.in/g_M3bpPs #HospitalityInnovation #AIinHospitality #Robotics #WorkforceDevelopment #FutureofWork #MarinaBaySands #GenAI #Leadership #Singapore #TheWayForward