Using sustainable technology to drive efficiency: Artificial intelligence as an information broker for advancing airline operations management

Abstract

Airlines are frequently confronted with disruptions that interfere with their flight operations, resulting in revenue losses and unsustainable performance. While information sharing is an important approach to mitigate airline disruptions, the industry is still characterized by technology fragmentation and a lack of real-time information exchange between actors in the airline ecosystem. As a response, this study investigates how artificial intelligence (AI could be utilized as an information broker to enhance information sharing for collaborative decision-making in airline operations management. Adopting a qualitative research approach, we conducted 22 semi-structured interviews with managers and professionals from three critical airline functions - air, ground, and information technology - across multiple global airlines to examine how AI is used for coordination and information sharing in their operation and how it impacts operational processes and performances. The results show that AI in the airline industry is in its infancy with fragmented applications within the airline ecosystem, but managers highlight the need for implementation of context-aware, organizationally aligned, and carefully integrated AI into operational routines. Our findings also show that in order to use AI as an information broker, most participants prefer an agent-based model for operations management, however, integrating agent-based models require advanced data that need to be collected from process-based systems first. We further discuss theoretical and managerial implications and provide actionable recommendations for implementing AI in airline operations. This is one of the first studies to specifically examine cross-departmental information sharing through AI from an information brokerage perspective.