AI and aviation
The revenues of all commercial airlines are predicted to reach almost USD 500 billion by the end of this year. And the corporations that are the most technologically advanced are leading the way. Therefore, the implementation of artificial intelligence in the aviation sector is a very topical issue. AI is changing the way companies approach their data, the operations they perform, as well as their financial flows.
There are several possible areas in aviation where artificial intelligence could prove very, very useful:
- Fleet and operations management. The use of AI-based systems will help to reduce operational and overhead costs by optimizing paracs and operations. Neural networks can help organize and optimize dynamic pricing. They are also critical for predicting force majeure, taking into account weather conditions, what is happening at other airports, etc., because AI can process huge sets of data in real-time at a time.
- Flight management. AI can be used to select optimal flight routes, develop an ideal schedule to help plan flights intelligently, and reduce operating costs. AI can also be used to prevent travel disruptions, schedule crews, and detect fraud.
- Customer service and retention. AI has the power to improve service quality by optimizing pricing strategies, increasing customer interaction, and improving overall flight quality. In particular, by tracking behavior, metadata, and purchase histories, neural networks are able to make tailored offers to customers, which is greatly appreciated by potential customers. AI can also analyze sentiment on social media to gauge customer reactions in real-time to improve the quality of service. And with chatbots and automation systems, trips can be scheduled online and contact center processes can be semi-automated to improve agent efficiency.
An important area of work for artificial intelligence in aviation is security. Facial recognition methods and biometrics pave the way for entirely new and unprecedented methods of emergency prevention. Also, a similar approach could be used by airlines to track the movements of people around the airport, allowing a better understanding of the flow of travelers.