Takeaway: Aviation is starting to adopt AI in many ways in order to streamline business and improve customer experience.
The aviation industry, especially the commercial aviation sector, is constantly striving to improve both the way it works and its customer satisfaction. To that end, it has begun using artificial intelligence. Though AI in the aviation industry is still in the nascent stage, some progress has been made already as certain leading carriers invest in AI. To start with, certain use uses are being implemented such as facial recognition, baggage check-in, customer queries and answers, aircraft fuel optimization and factory operations optimization. But AI can potentially go far beyond the current use cases. To make a long story short, AI can redefine how the aviation industry goes about its work. (To learn more about AI in business, check out 5 Ways Companies May Want to Consider Using AI.)
The Context
The global aviation industry has been growing exponentially. Take the example of the U.S. commercial aviation industry: In the next two decades, passenger count is expected to double. In 2016, the U.S. commercial aviation industry generated an operating revenue of $168.2 billion. This is an opportunity for exponential growth which needs to be handled well. The aviation industry needs to move beyond its present ways of working and find better ways to optimize resources, improve customer satisfaction and safety records, control costs and be more responsible environmentally. Data is key to unlocking the potential, and the aviation industry must leverage AI. So, while both the business case and context of AI in the aviation industry is set, we need to discuss the use cases being implemented currently.
AI Use Cases in Aviation
As already stated, AI in aviation is in the nascent stage, but some use cases are already being implemented by some major U.S. carriers. These use cases are described below.
Passenger Identification
The idea is to have machines perform end-to-end passenger identification and check-in at the airport. Delta Airlines has been testing this process. Delta has been keen on using AI for some time, as is evident in its initiatives such as ticketing kiosks and check-in via the Fly Delta mobile app. In May 2017, Delta announced it was going to invest $600,000 in four automated self-service bag checking kiosks, including one that will also have facial recognition technology. The experiment is being carried out at Minneapolis-St. Paul International Airport. According to Delta, previous experiments have helped streamline customer flow at the airport and improve customer satisfaction scores. According to the Delta annual report:
We are dependent on technology initiatives to provide customer service and operational effectiveness in order to compete in the current business environment. For example, we have made and continue to make significant investments in delta.com, mobile device applications, check-in kiosks, customer service applications, airport information displays and related initiatives, including security for these initiatives.
Baggage Screening
In 2017, American Airlines conducted an app development competition with the goal of having an app developed for making baggage screening easier for passengers. The competition, named HackWars, was themed upon artificial intelligence, dronesand augmented and virtual reality. The winner, known as “Team Avatar,” developed an app that would not only allow passengers determine their baggage size before arriving at the airport, but also prepay any potential baggage-related expenses.
Customer Assistance
United Airlines is using Amazon’s Alexa to have certain common customer queries answered. In September 2017, United announced a collaboration with Alexa. The feature is known as the United skill. To get started, all passengers need to do is to add the United skill to their Alexa app and then start asking questions. Alexa answers common queries correctly, such as the status of a flight by number, check-in requests and availability of Wi-Fi on a flight. The reviews so far have been mixed, which points to the fact that there is a learning curve, and it is still a long way to go before AI can fully handle customer assistance.
Challenges and Tasks
Since the aviation industry has only recently embarked on the AI journey, fully embracing AI is going to be a challenging task. The following challenges come to mind. (For more on current AI uses, see What AI Can Do for the Enterprise.)
Data Confidentiality Management
Humongous volumes of data will be in use as the aviation industry embraces AI, and that will give rise to data confidentiality risks. However, the need to properly manage data isn’t exactly a new challenge for airlines. One incident has already come to light, when it was revealed that Emirates, a leading airline, leaked customer data to third parties without authorization. It was found that customer details such as name, email, itinerary, phone number and even passport number were shared with third-party service providers such as Boxever, Coremetrics, Crazy Egg, Facebook and Google. Though Emirates policy states that there will be some data sharing, the policy is pretty ambiguous.
Tracking Progress
Tracking progress is an enormous challenge that airlines will face. The first thing they need to do is to develop analytics that will help them develop and process accurate data. However, that in itself is a challenge. What kind of analytics will help? For example, customer satisfaction is going to be one of the most important factors in success. What kind of analytics will determine that airlines have been improving on customer satisfaction parameters?
Managing Investments
AI needs huge investments, and probably the biggest risk in this is that smaller, especially budget airlines are going to miss out on reaping the benefits of AI fully. Does that mean that the performance of the smaller carriers will be impacted? That might not be the case, because we might be moving toward more acquisitions and mergers. Bigger airlines will have a massive appetite for acquiring smaller airlines with an eye on the market. It is not all gloom and doom though, because smaller airlines like Southwest have already shown some initiatives toward embracing AI.
Conclusion
It is surprising that a sector as important as aviation has woken up to AI so late. As AI in aviation picks up its pace, there could probably be a few mergers, acquisitions or even closure of small airlines which will not be able to afford the investments. Now, AI seems the best option to take aviation to the next level.
[“Source-techopedia”]
