The main applications of AI and data science in the airline industry

1. Revenue management

Revenue Management (RM) is an application of data and analytics to define how to use the right channel for those who need a product, at a reasonable cost at the right time.

This is based on the idea that customers perceive product value differently, so the price they are willing to pay depends on the target groups they belong to and the time of purchase.

Revenue management professionals make good use of AI to define destinations and adjust prices for specific markets, find efficient distribution channels, and manage seats to keep the airline competitive and customer-friendly at the same time.

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2. Air safety and airplane maintenance

Airlines bear high costs due to delays and cancellations that includes expenses on maintenance and compensations to travelers stuck in airports. With nearly 30 per cent of the total delay time caused by unplanned maintenance, predictive analytics applied to fleet technical support is a reasonable solution.

Carriers deploy predictive maintenance solutions to manage data from aircraft health monitoring sensors better.

3. Feedback analysis

Air travel can also be stressful for the more frequent and experienced travellers who are leaving passports with clean pages. They have to do many things like checking bags or finding a gate and taking a selfie before getting into the plane seat!

In this regard, airlines can improve customer service by learning about the airport's pain points and flight experience through data analysis. Using AI for feedback analysis and market research allows airlines to make informed decisions and meet customer expectations.

4. Messaging automation

When interrupted, such as flight delays or loss of luggage, travelers become nervous. If customers do not receive a timely response or clarification from an airline representative, they cannot choose this airline for their next trip. The speed of response to customer queries is similar to the actual steps taken to solve the problem.

AI solutions, speeds up and simplifies the workflow of customer service employees by using algorithms to process natural language or structured text. The potential solution can be developing a chat bot

5. Crew management

“Crew management is a complex task due to many legal constraints. For instance, if staff belong to a trade union, limitations include an allowed number of flight hours and days off, as well as reimbursement in case of a labor law violation,” сlarifies data scientist Konstantin Vandyshev.





6. Fuel efficiency optimization

Global Aviation generates nearly 2 per cent of anthropogenic carbon dioxide (CO2) emissions. That is why aircraft manufacturers and carriers are trying to improve their fuel efficiency. Airlines use AI systems with built-in machine learning algorithms to collect and analyze flight data related to each route distance and heights, aircraft type and weight, weather.

7. In-flight sales and food supply

Getting relaxed by watchin gblue clouds from flight might be a dream but here you can utilize AI were supply chain specilists can define how many food and drinks they must onboard without being wasteful. AI is here to help, too.





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