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7 ways AI will revolutionise business travel

James A. Martin | June 7, 2017
From chatbots to robotic bellhops, AI and machine learning are already having an impact on how we travel for work and pleasure.

But with the next wave of applications, “we’ll start seeing major improvements in the business travel experience,” Singh says. “This wave will be AI interventions built on cognitive computing. These systems will have the ability to understand, learn and reason through the enormous data and then provide solutions that a human agent won’t be able to provide on their own. These systems would provide value-added services and experiences, which would cognitively not be possible for the average employee in the travel industry.”

The travel industry can use AI and machine learning “to learn about the habits and preferences of its frequent fliers and guests, to provide more personalized experiences,” says Sumit Gupta, VP of HPC, AI and analytics at IBM. “Imagine the day when you can sit down in your seat and the flight attendant already knows just how you like your gin and tonic. Then, you’re greeted at the hotel desk by name because of visual recognition software. And the Yankees game is already playing on the TV when I arrive in my room.”

Wayne Thompson, chief data scientist at analytics software developer SAS, paints the following picture of AI-assisted business travel in the future:

“Let’s say you have an important customer briefing in Los Angeles,” Thompson explains. “You’ve already received a text that your flight is on time. Monday morning is one of the busiest times at the airport, and naturally you’re running late. You start to worry about finding a spot to park in the packed airport garage, but then your navigation system uses image detection to direct you to the best open spot. Using convolutional networks, the computer can analyse photos of the parking lot in real time and detect images with a 6 percent error rate, which is better than the human eye.”

Once you pass through airport security, “you’re back on track timewise and decide to get a coffee and something to read,” Thompson continues. “While approaching the book store, you’re notified of special promotions based on your reading history. Then, at checkout you receive a coupon for gardening and classic car magazines, based on a recommendation system that knows these are your hobbies.

“Now you’re starting to wonder why your co-worker hasn’t arrived at the gate. She receives a warning that she was in the wrong terminal and gets instructions on the quickest route to the correct gate. Location services have long been used to route planes. Now, they can also be leveraged to better move passengers along and help assure that flights are on time.”

Once you’re in the air, you use the airplane’s Wi-Fi to tweet something like: “RDU > LAX leaving on time. No complaints here. First leg of this busy travel day could have been ugly but was not.” Using entity extraction and sentiment analysis software, the tweet is interpreted as positive, so the airline responds: “Thanks! We hope the rest of your day goes as smoothly. Should be sunny and 80 in LA when you arrive.”


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