AI & the future of hospitality, tourism and leisure

A digital concierge answers guests' questions by chat, messaging app, phone or a screen in the room, in the guest's own language and at three in the morning too. Real-time translation through earbuds and screens already lets a receptionist and a guest understand each other without a shared language. The next step is a concierge that takes action: it books the table, orders the taxi and moves the spa appointment when the flight is delayed. Translation, meanwhile, becomes invisible. Subtitles in lightweight glasses, or earbuds that keep the speaker's own voice, let a guest hold a whole conversation in their own language, and let a kitchen team with five first languages work together with ease.

AI weighs the pace of bookings, prices nearby, flight schedules, the weather and events in town, and can change a rate several times a day. Theme parks, museums and sports clubs work the same way with variable prices and time slots. The revenue manager sets the strategy and the limits: how high a price may go, and which agreements with regular guests and groups apply. Next, pricing covers the whole stay. AI sets a price for the room, breakfast, parking, spa and late check-out for each guest and each moment, and takes into account what a guest is worth over the years. When the guest's AI agent does the booking, the price becomes a negotiation between two systems.

AI uses earlier room choices, requests and reservations to predict what this guest will value on their next stay, based on the preferences they have shared. It then suggests something that fits: a quiet room for the business traveller, an early table for the family, a late check-out for the guest flying home on Sunday. Rewards follow the guest's own travel habits as well. The next step is a room that adjusts to the guest. Lighting, temperature, pillow, minibar and the art on the screen are set the way they like on arrival, even at a different hotel in the same chain.

An AI agent completes a task by choosing the steps itself and using the systems it is connected to, within limits the business sets. A guest calls to add a night to their stay: the AI agent checks availability, works out the price, amends the booking and sends a confirmation. Voice agents that take and change reservations are already in use in hotels; other AI agents process group enquiries or build rotas around expected demand. In time, one layer of AI agents will connect every system. Bookings, tills, housekeeping and maintenance then work as one: the AI agent releases a room as soon as it has been cleaned, and books the engineer when a tap starts leaking.

Smart kitchen systems tackle food waste from two sides. A camera above the bin recognises what is being thrown away, and scales underneath weigh how much. The chef can see which dish, or which part of the breakfast buffet, is regularly left over. AI also forecasts how many guests will turn up, using reservations, occupancy, the weather and previous years. Kitchens that measure this way often report a clear drop in waste. The next step is a kitchen that does its own buying: AI orders from suppliers based on the forecast, adapts tomorrow's menu to what is left and sends surplus on to its next use. After that, each plate can be matched to the guest's nutritional profile.

AI forecasts crowds from ticket sales, reservations, the weather, holiday periods and sensor counts. Theme parks, museums and events spread visitors with time slots, off-peak prices and a quieter route in the app. Across a whole destination, public authorities use similar data to plan transport, access rules and campaigns. The next step is a digital twin of the whole destination, which models crowds days ahead and steers them with daily quotas and entry fees that move with demand. Since 2024, a busy historic city has been trialling an entry fee for day visitors on selected days, so residents can keep their city liveable and visitors have a better day.

In hotels with mobile check-in, the first contact with a member of staff moves to a moment the guest chooses. That gives reception a different role in the stay. AI combines arrival times with housekeeping progress, so guests know sooner when their room is ready, and picks an available room that matches their wishes. The team can see which arriving guests need personal attention, for instance because of a special request or a delayed journey. A digital key on the phone opens the door as soon as the room is available. Staff welcome guests out on the floor, while the paperwork happens in the background.

Many hotels already have delivery robots that call the lift themselves and drop off a towel or a toothbrush. Cleaning robots do the corridors and lobby at night, and some kitchens have robots that fry, stir or make coffee. Cameras, sensors and AI let such a robot read its surroundings, so it steers around a pushchair and slows down when someone walks in front of it. When staff are short, the robot takes over the repetitive work. Staff spend less time delivering and cleaning, and more time with guests and on the problems no system foresaw.

In a smart hotel, the systems know when a room is occupied. Sensors measure presence, temperature and air quality, and AI controls heating, cooling and lighting per room based on bookings and behaviour: an empty room is not cooled, and the room of a guest arriving at four is at the right temperature in time. The same data shows when equipment needs servicing, before a guest ends up in a hot room. Hotels could then start trading energy. AI runs solar panels, a battery and heat storage hour by hour: charging when power is plentiful, feeding it back when the grid is under strain. A hotel also becomes a small power station.

Planning, enquiries, routine questions and forecasting demand: in an AI-first organisation, AI, AI agents and robots do the work people don't need to do. Staff concentrate on what a guest remembers: personal contact, attention and a solution when something goes wrong. At the busiest moment of the week, AI has already predicted the rush and an AI agent answers the phone, so the team has time for the guest with an unusual request. Staff get more room to read a guest, give advice and make a moment special. Around 2040, such an organisation could run on a small permanent team working alongside AI agents and robots.

When guests check themselves in and an assistant answers the routine questions, the work at the desk changes. The receptionist becomes a guest host: walking the lobby, recognising guests, solving problems and making sure everything about the stay is right, from arrival to departure. Roles that barely exist today appear as well. The trainer of the hotel's AI agent teaches this digital colleague how the hotel speaks to guests, how to handle unusual requests and when to call in a person. The night-shift lead directs the robots and humanoid robots that make up the rooms. And at the resort, a longevity coach guides guests through a programme that carries on at home. Staff gain new career paths, including those who once started behind the desk.

A picture of the future only means something once staff see what it changes in their own work. Leaders in hospitality take the initiative on AI and new technology, and turn where the business will be in five or ten years into steps everyone understands, from the kitchen to reception. They start with small changes that everyone can see, leave room to experiment and involve staff in the ideas, so the team builds the future together. Even when AI agents and robots join the work, leaders give their people direction and room to move.

In a future academy, an organisation prepares its people for the future instead of waiting for the education system to do it. Current staff learn what AI, AI agents and other new technology change in their work, and how to work with them. New colleagues learn from day one to work alongside AI. Leaders practise deciding which work goes to people and which to AI. The lessons come from daily work and grow with the technology.

A customer rarely experiences a single organisation. They experience a chain of businesses and services, and judge the whole. Organisations therefore work more and more as an ecosystem, in which partners, start-ups, scientists and public authorities tackle shared problems such as crowding, staff shortages and sustainability. A joint forecast of visitor numbers helps everyone plan better. Partners can test an approach from abroad together and adapt it to their own work, so customers feel the difference sooner.