How Hotels can Adopt Artificial Intelligence Without Losing the Human Touch

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How Hotels can Adopt Artificial Intelligence Without Losing the Human Touch

M Social Hotel Singapore was first in Asia to pilot an autonomous service delivery robot AURA in 2017, developed by Savioke. Photo: Millennium Hotels & Resorts. Right: Koo Ping Shung

By Koo Ping Shung, 11 March 2022

Sci-fi movies and recent advancements in technology have sustained a fascination with Artificial Intelligence (AI), and businesses are keen to integrate Artificial Intelligence into their processes. But before we discuss AI applications in the hospitality industry, let’s look at the current AI landscape.

Confusion

Right now there is a lot of confusion over the term ‘Artificial Intelligence’.

When the term was coined, it referred to a human-level kind of intelligence, the kind of AI you are likely to see in movies such as Jarvis or Friday in the Marvel Cinematic Universe. This level of intelligence is the holy grail among AI scientists and is now commonly known as Artificial General Intelligence (AGI).

But what most of us are seeing right now is known as Artificial Narrow Intelligence or, to put it in a more layman term, is “smarter automation”. Why smarter automation? Because the current level of technology allows agents, software or robots to perform well in a specific task in a stable environment. For business folks, this means better tools for automation. 

The hospitality industry can potentially exploit these smarter automation tools to reduce the pressures brought about by the current human resource crunch.

Potential Areas

But how should the hospitality industry determine which areas or processes can be automated?

The first consideration goes back to business value. Hotels and resorts have to ask the critical question, “Is a human touch needed?” If the answer is “No,” then perhaps they can explore AI for automation.

Let me give an example. I have observed that some hotels have replaced their check-in with a computer agent, instead of a human receptionist. As a traveler, if I am checking into a high-end hotel, I will expect the “human touch” of a receptionist because I might have tons of other questions to ask, such as where breakfast is served, or make a request for a room with a nice view. If, however, I am checking into a budget hotel, perhaps the computer agent will suffice. 

Another example is having a robot cook an omelet in the hotel. If the hotel is high-end, most guests will prefer their omelet to be prepared with a human touch. 

In short, non-guest-facing processes such as hotel security or facilities sanitization can potentially be automated further, but hotels and resorts should consider carefully the need to automate guest-facing processes.

Failure Alert

One of the biggest failures of AI projects is that they cost a lot more than the value they bring.

To assess whether or not a process can be automated with AI, it’s best to have an AI professional who has the technical knowledge, experience and some business knowledge. Each project is unique, and it takes a trained and experienced person to determine if automation is possible and if the cost of implementing it is worth it.

Adopting AI is only the start. There are costs of maintenance to consider, which can be time- and money-consuming, not forgetting that the hospitality industry’s job is to take care of travelers and guests, rather than robots and software.

The first AI project will always be the most important as it will determine if AI will be adopted in other parts of the business. Thus, it is of utmost importance that the first project pulls through greatly.

Conclusion

I believe the hospitality industry can adopt smarter automation or Artificial Narrow Intelligence to help ease its manpower crunch. However, what’s critical is still for it to preserve or increase its competitive advantage, which is the “human touch” and being able to exceed guest expectations.

About

Singapore-based Koo Ping Shung has more than 17 years of experience in Data Science and Artificial Intelligence. His work spans the data value chain, from data collection, data management and data governance, through to the implementation.

Koo advises companies across various industries and is an instructor at institutions such as the National University of Singapore, Singapore Management University and ESSEC Business School. He is co-founder of DataScienceSG and is president of AI Professionals Association and AI Singapore’s Industry Innovation Mentor.