Passenger perceptions of Artificial Intelligence in airline operations: Implications for air transport management

Fondevila-Gascón, Joan-Francesc, Gutiérrez-Aragón, Óscar, David Lopez-Lopez, Gonzalo Curiel-Barrios and Alabart-Algueró, Júlia

Journal of Air Transport Management, 2025, vol. 129, issue C

Abstract: Artificial Intelligence (AI) is reshaping the aviation industry, driving efficiency, automation, and innovation across multiple operational domains. This study examines commercial airline passengers’ perceptions of AI’s role in addressing key industry challenges, including air traffic management, predictive maintenance, passenger experience, and sustainability. Using a quantitative approach, a survey was conducted among 320 airline passengers in Spain to assess their attitudes toward AI-driven applications in aviation. The findings reveal strong support for AI in optimizing flight operations, reducing delays, and enhancing security procedures. However, significant skepticism remains regarding AI’s autonomy in decision-making, particularly in pilot replacement and automated flight rerouting. Statistical analyses indicate that younger and frequent travelers exhibit higher confidence in AI’s potential, whereas older passengers demonstrate greater reluctance toward AI-driven automation. Additionally, AI is perceived as a crucial enabler of environmental sustainability, with respondents acknowledging its role in reducing fuel consumption and emissions. These insights provide valuable implications for policymakers, airlines, and technology developers seeking to align AI adoption with passenger expectations while ensuring safety, efficiency, and regulatory compliance. The study highlights the need for a balanced approach that integrates AI’s technological advancements with human oversight to foster trust and acceptance in the future of AI-powered aviation.

Keywords: Artificial Intelligence; Air traffic management; Predictive maintenance; Passenger experience; Aviation sustainability (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jaitra:v:129:y:2025:i:c:s0969699725001371

DOI: 10.1016/j.jairtraman.2025.102874

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