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<52% of Airlines Plan to Adopt AI Technology Within the Next Three Years — How Will This Change Our Travel Experience?> Featured Article

52% of Airlines Plan to Adopt AI Technology Within the Next Three Years — How Will This Change Our Travel Experience?

by  Kao Ching-yuan 2017.09.18

Source: https://www.bnext.com.tw/article/46208/airports-turn-to-ai-for-better-customer-service?utm_source=line&utm_medium=message&utm_content=20170918

Image source: pixabay

Air travel is a common experience for people today. Beyond improvements to aircraft performance and cabin design keeping pace with the times, statistics show that 45% of airports and airlines plan to introduce AI and chatbots within the next five years. Beyond the most direct impact on passenger services, how else might this transform the future of air travel?

Air travel is a universal part of modern life. According to a recent study by the International Air Transport Association (IATA), a growing number of airports and airlines are embracing the latest technology, leveraging artificial intelligence (AI) and chatbots to optimize operations and improve passenger services. The aviation industry is poised for significant transformation with the integration of new technology over the next decade — so just how will AI reshape the world of aviation?

45% of Airports Plan to Invest in AI and Chatbots Within Five Years to Handle Large Volumes of Customer Service Requests

It is almost impossible to imagine the future without AI, and the aviation industry is actively moving in that direction. According to IATA research, 45% of airports plan to invest in AI development within the next five years, while 52% of airlines plan to adopt AI technology within the next three years. Both aim to leverage technology to improve services and the passenger experience. It is estimated that 80% of airlines plan to invest resources in predictive alert systems over the next three years — all of which will rely on AI.

Another development capturing the industry's attention is chatbots. Currently, 14% of airlines and 9% of airports have already implemented chatbot applications, enabling them to quickly and efficiently handle the surge in customer service requests related to ticketing and itineraries when poor weather causes widespread flight disruptions. The report shows that the aviation industry's demand for new technology will grow increasingly over the next three years, with 68% of airlines and 42% of airports expected to adopt AI-powered chatbot services by 2020.

Optimizing Sales Through Mobile Services

Mobile app services are also a key focus for the future development of the aviation industry. The report notes that over the next three years, 94% of airlines and 82% of airports will prioritize app development plans.

Many industry players are concerned with how to influence sales — both directly and indirectly — through mobile services and how to commercialize them. Airlines hope that mobile sales will account for 17% of total sales by 2020, simplifying complex services into a single app to deliver a seamless experience. IATA CTO Jim Peters said: "We know passengers tend to embrace new technology. If well-designed, it can truly transform the passenger experience by assisting with sales and passenger services — and that is what mobile apps and AI can achieve."

Currently, nearly three-quarters of airlines use in-house developers to build their apps, while 42% hire external developers or partner with technology companies. Peters added, "Combining external and internal teams in development ensures that new products integrate technological capability while retaining aviation expertise."

How Will Technology Change the Flying Experience?

Taiwan, situated in a region of intense typhoon activity, is no stranger to weather-related flight disruptions. From basic security screening to predicting flight delays, how will new technology change the way we travel over the next decade?

Predicting Flight Conditions in Advance

Weather and mechanical failures can both affect flights, and most passengers are understanding about force majeure situations — but spending hours waiting at the airport is an absolute nightmare. If airlines can integrate machine learning with big data to replace on-the-spot human judgment with advance analysis, they can prepare for problems before they occur and notify passengers before they even arrive at the airport, avoiding the ordeal of waiting with no certainty about when the issue will be resolved.

Rapid Identification of Suspicious Passengers

Nearly all major airports are equipped with thermal imaging cameras to measure passenger temperatures upon entry and exit. In the future, these can be further combined with facial recognition to analyze passenger movement throughout the airport, enabling rapid identification of suspicious luggage or individuals in even the largest terminals.

Improving Security Screening Efficiency and Accuracy

Passport inspection during security screening is time-consuming and labor-intensive, yet it serves as a critical line of defense for national security. Although automated passport clearance is already widely used at many airports, it is largely limited to citizens of the respective country, and the vast majority of travelers still undergo manual inspection.

In the future, by incorporating supervised learning, models can be built from training data to infer new instances — in simple terms, this means scanning the photo on a passport and linking it to a personal ID for rapid data verification, and even collecting passengers' social media data online to serve as a first-line counterterrorism screening tool, improving both speed and accuracy. Adding cluster analysis would further enable the system to flag passengers with prior adverse records for additional manual review.

Additionally, passengers carrying large amounts of carry-on luggage require considerable effort from security staff to inspect. By combining machine imaging and analysis, suspicious items inside luggage can be quickly and repeatedly identified without opening the bag. After using supervised learning algorithms to collect substantive training data, AI can flag items that require a secondary manual inspection.

New technology applications can reduce human error, improve efficiency, and enhance service satisfaction. Most importantly, all of these advances are built on combining the strengths of human capability. As we observe the application of new technology, let us not forget the "human touch" in service — for that may well be the most memorable part of every journey.


 

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