Applications of Data Science and AI in Airline Operations

Applications of Data Science and AI in Airline Operations
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There’s no denying that technology continues to change the way businesses make strategic choices, build workflows, and interact with consumers. For example, actions like booking flights using applications on mobile devices have become relatively common today. Through real-time data access—the oil of the 21st century—organizations are able to make informed decisions to ensure operational efficiency.

In this article, we’ll discuss how the players in the airline industry leverage cognitive technologies so that they can soar to new heights. Continue reading if you want to know more.

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The primary applications of data science and AI

The cognitive technologies of artificial intelligence that transform data into actionable insights can automate and streamline analytics, customer service, machinery maintenance, and various tasks and internal processes, making them useful in airline operations management.

  • Revenue management – Revenue management refers to the application of analytics and data aimed at determining the ideal approach to sell your offerings to the intended audience at the best time and channels at reasonable costs. It’s based primarily on the thought process that consumers perceive the value of products and services differently. Thus, the amount they’re willing to pay for will depend on which target group they’re in. Experts in revenue management utilize AI technology to adjust prices and define destinations for targeted markets, find more efficient channels of distribution and manage their seats to ensure their airlines remain customer-friendly and competitive.
  • Airplane maintenance and safety – It’s not uncommon for airlines to bear high expenditures because of cancellations and delays, including the costs associated with compensations for travelers and maintenance concerns. With almost thirty percent of delays due to unplanned maintenance, the use of predictive analytics for the technical support of the fleet is a practical solution. Predictive maintenance solutions are deployed by carriers to ensure that data is managed better from the monitoring sensors of the aircraft. Since these systems are often compatible with mobile and desktop devices, relevant personnel can access historical data in real-time from anywhere. And by understanding the technical conditions of the aircraft via reports, reports, and notifications, it’s possible to find problems and address issues proactively.
  • Feedback analysis – Not many realize how stressful traveling can be, especially for those who frequently go on trips. After all, they need to do a lot of things, from checking their luggage to finding the right gates. But with data analysis, airlines acn learn about the traveler’s pain points. AI-powered feedback analysis can enable them to make smart decisions, ensuring they meet customer expectations by finding opportunities that will make the experience better. 
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Artificial intelligence and data science are increasingly becoming commonplace in businesses across all sectors, and the airline industry is no different. They serve many different applications, ranging from revenue management to feedback analysis. In doing so, they’re able to improve customer satisfaction, streamline operations, and reduce their expenditure significantly, raising the profit margins in turn. Because of all its advantages, it’s only a matter of time until every airline company begins to adopt these technologies and practices.