Are robots coming to a hotel near you?
13 experts shared their view
A recent University of Houston report on robots in hospitality claims that by 2030 over a quarter of hospitality jobs will be replaced by robots. Will robots ever replace all humans in hospitality? Next-gen technology will undoubtedly replace mundane, repetitive, and dangerous jobs in hospitality performed by housekeepers, porters and baggage handlers, concierges, security guards, line cooks, room service, bartenders, waiters, etc. Some hoteliers claim that hospitality is an industry of "people serving people" and robots will be playing only a marginal role. Others, citing the high labor costs which constitute as much as 50%-84% of overall hotel costs in these low travel demand, low occupancies era, predict that robots will replace humans in all dangerous, repetitive and mundane jobs at the property.
The question is, are robots coming to a hotel near you anytime soon?
The use of robotics in travel is a controversial topic, often even mocked, due to what, I believe, is a fundamental misunderstanding. Whenever we talk about robotics in travel, we do it with a certain degree of superficiality. The application of robotics in hotels remains sporadic at best, and most guests tend to perceive it more as an attraction (such as a Disney avatar in a theme park) rather than a real problem-solver. And here, in my opinion, the misunderstanding arises. Technology is never the end, but a means to improve internal processes, build branding, guest loyalty and increase profits. However, in hospitality, robots contend with humans for a job that does not necessarily suit them, made of complex nuances, hard to understand by non-biological entities. The hotel of 2030, in my opinion, will not be populated by androids such as the case of the Hen-na hotel, but by invisible, "human-enhancing" technologies (AI, AR, VR, blockchain, open API, etc. ) at the service of biological employees. And, when the latter will be, eventually, replaced by robots, it will likely be in areas where machines tend to perform better (back office, revenue management, distribution, prediction, luggage transportation, self-service, etc.), rather than in more "human" areas (such as the interpretation of the nuances of human communication, for example).