AI On Time? Evidence from Curb-to-Gate Facial Recognition

Problem definition: This paper examines the influence of an artificial intelligence (AI) application – facial recognition technology at airports – on flight on-time performance. While facial recognition at airports has the potential to save time during check-in and boarding procedures, flight departures could be delayed due to recognition errors and system inaccuracies of this immature technology. Therefore, the impacts of facial recognition on flight on-time performance remain uncertain and require rigorous empirical investigation. Methodology/results: In this study, we exploit the first terminal-wide implementation of facial recognition in the U.S. and examine its impact on flight on-time performance. Our analysis of flight-level data reveals approximately a 16% reduction in departure delays and a 6% reduction in arrival delays but no increase in early departures or early arrivals. Interestingly, the improvement in on-time performance is smaller for flights to destinations in Asia and Africa, which tend to have a higher proportion of non-Caucasian passengers, but more pronounced for flights with larger seat capacity. Managerial implications: These findings demonstrate that implementing AI tools such as facial recognition can enhance operational efficiency and reduce flight delays on average. However, the magnitude of benefits varies across flight destinations and aircraft sizes. These findings offer valuable insights for firms that are considering the deployment of AI technologies for operational efficiencies.