AI improves the customer experience by optimizing and personalizing airline services.

 

Aviation context.

Challenges more specific to commercial air transport include social acceptance of AI (including workforce empowerment such as pilots, flight crew, maintenance, logistics), trustworthy AI (i.e. explainable, robust, reliable, secure, and ethically aligned), human-AI teaming, employee upskilling (e.g. availability of skills and training needs), and State-level AI sovereignty (e.g. questions of partnerships and collaborations). On a more technical side, risks also concern the development ofembedded hardware and associated AI infrastructure (considering the required investments), cybersecurity (especially for onboard and ground operations), and, last but not least, data strategy—as data is the fuel that feeds AI models. Often mirroring the risks, several opportunities also arise. First and foremost, AI presents a sound opportunity to assist, augment, and support employees, rather than replace them. It allows humans to focus on more complex and rewarding tasks. Frugal AI is a promising technique that aims to achieve high performance whileminimizing resource and data consumption, making AI more sustainable. Simpler methods requiring less data must be prioritized in research. AI should not be a default choice when it is not needed. Sustainability and societal impact should be metrics to prioritize AI applications. Generative AI also presents opportunities for improving operational efficiency (e.g. widespread integration of coding tools, enhanced knowledge management). AI can enhance safety andincrease automation in the aerospace industry—critical priorities. AI also enables predictive maintenance and health monitoring, often using simple algorithms with minimal computational requirements. Finally, AI improves the customer experience by optimizing and personalizing airline services