AI Applications in Tourism: Current Status and the Future Expectations

Last week I and a chance to be a part of a conference about Tourism and its different Tech and AI aspects. In Croatia, tourism is a significant industry, so it made sense to analyze some data and propose some conclusions.

In general, research from 2017 onwards is showing that Tourism, is not one of the top adopters of AI. Together with health care /about which I wrote a bit in my article about AI and Diabetes) and education, it was in the category of low adopters. If we are looking at the companies in a certain industry, it is observable that although there are some advancements, in comparison to others, the Tourism/Travel industry is lagging behind. That is unsurprisingly correlated with the level of investment, and future investment plans for different industries. Leading industries in both adoption and level of investment are high tech and telecommunications, automotive and financial services.

What is interesting is that if looking at the potential value AI can bring over other analytic techniques, Tourism/Travel is ranked first (according to McKinsey research). It is followed by transport and logistics, retail and automotive. Additionally, when looking at the cross-sector potential, to create additional value, again Tourism is again a frontrunner.

Researchers identified different areas of application, such as:

Facial recognition for fast and document free sign-ins and passes

Virtual reality — assess the ambiance & environment of the hotel

Chatbots — applied in Marriott hotels, Hyatt hotels, GRT hotels…

Robots — turning on the bedroom lights, turning off the television, handling systems to ensure the luggage is checked in automatically, and receiving the guests in a hotel

Language translators — allow travelers to converse with the local people in their language. Google Translate provides the audio speech services when the traveler clicks on the option, “Conversation mode”

Of course, we should not forget that AI is a both value-adding or value-destroying resource in its role in human experience encounters within service ecosystems. Recent research on AI highlights potential negative aspects. These aspects range from job loss to privacy concerns, machine ethics, security issues, and negative developments of potential superintelligence.

Some researches identify 3 main focus areas:

Hospitality and Gastronomy (with check-ins and check-outs, smart rooms, back office management, etc.)

Destination Management Organization (Robots, Chatbots, assistance in the decision-making process, etc.)

Airports, Theme Parks, and others (service automation, tourist flow analysis, autonomous trolleys, etc.

Big data is of course a significant part of those projects. Tourism businesses use AI and big data to connect guests creatively and meet their expectations with personalized service. It enables tourism professionals to learn more about their customers, and the more they know the better experience they can offer to customers.

There are some downsides to that. Because of personalization, it could be difficult to appreciate services if only perfectly personalized ones are delivered. Some fear of loss of authenticity and that missing out on general offers might happen. It is not impossible that at the end of the cycle, as a response we could have AI-free destinations.

Fortunately, there is a number of applications already working in different segments that we mentioned, that could be used as an inspiration:

1. Vouch sells an AI-enabled digital concierge that’s designed to answer guest inquiries, make bookings and take room service orders — https://www.vouchconcierge.com/en/

2. Chatbots that are used by Airbnb, Booking.com, Skyscanner, and Expedia.

3. Travelstop that aims to simplify business travel with the help of its serverless SaaS platform, that’s designed to speed up the booking process, automate expense reporting and provide cost-saving insights — https://www.travelstop.com/

4. Hopper — optimal hotel prices and flights while offering users personalized recommendations about the most suitable time to book a flight — https://www.hopper.com/

5. Fooyo that creates customized itinerary planners that include real-time crowd monitoring for attractions and events — https://www.fooyo.sg/

6. Robots that were presented in the Hilton hotels, or at the Heathrow airport, or Henn Na hotel that only uses robots as personnel: https://www.hennnahotel.com/ginza/en/

7. And Mindtree who is monitoring your social engagement and using this data: https://www.mindtree.com/

8. SITA is used in airports for better baggage management: https://www.sita.aero/

We could conclude that the full potential of AI implementation across contemporary service ecosystems, particularly in the arena of tourism destination systems, is still far beyond reach.

But even more important is that there is immense potential for AI applications in Tourism and that every project starting now, will have a significant advantage over others who might come later. So my recommendation would be, to jump on that train as fast as possible. This is an especially good opportunity for the smaller countries like Croatia, since there is very limited competition, and initial investments and requirements are not as high as in other sectors.

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Aco Momcilovic

Aco Momcilovic

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Ph.D. Student. National AI Capital Researcher. Human Resoucres, Psychology, Entrepreneurship, MBA…