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  /  Artificial Intelligence   /  How Artificial Intelligence and Data Science are Redefining Airline Industry
Artificial intelligence and data science, artificial intelligence in airline industry

How Artificial Intelligence and Data Science are Redefining Airline Industry

Artificial intelligence and data science are optimizing flight operations in a huge way

The airline industry has been hit continuously by various situations in recent years. First, by the increasing fuel price and recently, by the Covid-19 pandemic that almost jeopardized the sector for a long time stagnating revenue flow. In critical situations like this, it is safe for airline industry to adopt technologies that are futuristic and will bridge the money flow. Artificial intelligence (AI) and data science are optimizing flight operations and hugely impacting the commercial aviation industry.

Airline passenger traffic keeps increasing over years. It is expected to double in the next two decades. Henceforth, to address the increasing challenges, the aviation industry must embrace disruptive technologies to keep pace with customer demand and improve operational efficiency, speed, and customer satisfaction. AI and data science in the aviation industry are transforming the way companies approach their data, operation, and revenue streams. The world’s front-running airline brands are already using artificial intelligence to improve operation efficiency, avoid costly mistakes, and increase customer satisfaction. The adoption is expected to spike with more people becoming aware of the features AI and data science brings. The market of AI in airlines is anticipated to reach US$2.2 billion in 2025, showing how much the industry is investing in this technology. Data science is comparatively no less to AI when it comes to leveraging futuristic opportunities. The aerospace flying high in the skies is generating a trove of data on engine systems, fuel utility, weather, passenger information, etc. Henceforth, GlobalTech Outlook brings you a list of AI and data science features that are proving their excellence.


AI at airport security screening

Artificial intelligence is being increasingly deployed at airports. It has the ability to process vast information about data and streamline tasks and procedures. AI is used to detect potential threats at major airports. For example, John F Kennedy and Los Angeles airports are using AI-powered biometrics technology to scan passengers. This AI-enabled tool will speed up the passenger identification process. Not just passenger screening, luggage screening is also important at airports. Japan’s Osaka Airport plans to install Syntech ONE 200, an AI platform to screen baggage for multiple conveyor belts.


Fleet and operation management

By powering fleet and operation management with AI, airlines can significantly reduce their operational costs. AI-powered systems help airlines to maximize revenues by optimizing their base published fare that has already been calculated based on journey characteristics and brand segmentation, and further adjusting the fare after evaluating details about the travelers and current market conditions. AI algorithms can also help optimize the sales revenue in the longer term to ensure all flights are optimally booked.


Better customer experience

Like many other industries, the core motto of airlines is to make customer experience smooth. Even though the current airline customer service is largely manual, airlines are anticipated to adopt chatbots services to address customer demands. For example, SnatchBot and Mindsay are front runners who advance airline experience by leveraging AI mechanisms to answer questions, take bookings and manage reservations.


Risk management

The aviation industry has been through risky situations constantly in recent years. These unstable times have made airline companies develop various data-related risk management models and strategies to protect themselves from being victimized. Data analytics can find crucial movements like constant change of time zones, long duty days, scheduling changes, etc. For example, developers of Crew Rostering solution from Jeppesen aims to provide schedulers with the ability to rely on data about predicted fatigue to reduce risks in the planning phase.


Messaging automation

It is the airlines’ responsibility to always stay in touch with customers and give immediate, proper and effective solutions to all his/her queries and grievances. When unfortunate happenings like baggage loss or flight delays take place, travelers get nervous and expect an explanation from the company. Currently, airlines are using automatic message service to acknowledge flight schedules and loss of baggage. For example, Coseer by Arbot Solutions, an AI-powered software simplifies customer service employees’ workflows by using algorithms for processing natural language and unstructured text.