Artificial Intelligence potential within airlines: a review on how AI can enhance strategic decision-making in times of COVID-19

Abstract

Purpose: Airline strategy relies on the competitive environment analysis and the management of resources. Artificial Intelligence (AI) algorithms are being increasingly deployed throughout several industries. COVID-19 has further stressed a sector where firms have historically struggled to sustain profitability. The purpose is to explore the potential of AI applications regarding strategic decision-making in airlines in times of crisis and to depict a roadmap to encourage scholars and practitioners to jointly implement these tools within corporations. Design/methodology/approach: This study firstly reviews the state-of-the-art regarding transport organization trends with focus on airline strategy and finance as well as AI tools, supported by the collaboration of a former airline digitalization strategist. Secondly, the potential of the latter to be applied in those functions is analyzed, considering different Machine Learning (ML) methods and algorithms. Findings: Some applications or pathways are identified as of particular interest for the airlines’ strategic decision-making process. Most of them are based on ML algorithms and training methods that are currently underused or disregarded in certain business areas, such as Neural Network models for unsupervised market analysis or supervised cost estimation. Research limitations/implications: Focus is on airline strategy and finance, keeping engineering or operational applications out of the scope. Practical implications: Proposed guidance may promote the deployment of AI tools which currently lack practical implementation in certain business areas. Social implications: Showcased guidance may revert into a closer collaboration between business and academia. Originality/value: Comprehensive review of current airlines’ strategic levers and identification of promising AI pathways to be further explored.

Keywords

• artificial intelligence, machine learning, airlines, strategic decision-making, covid-19