Impact of AI Security Technology on Performance Efficiency in ABU Dhabi Airport

Abstract

In response to escalating global security demands and the rapid advancement of digital technologies, international airports are under increasing pressure to modernize their security infrastructure without compromising operational efficiency. Abu Dhabi International Airport, as a leading aviation hub in the Middle East, provides a strategic context for evaluating the transformative potential of Artificial Intelligence (AI) in enhancing security performance. This study examines the impact of AI-based security technologies on performance efficiency at Abu Dhabi International Airport, with a focus on the mediating role of technology adoption. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), the research analyses data collected from airport security personnel to assess both the direct and indirect effects of AI implementation on operational performance. The findings reveal that AI-based security technologies significantly enhance both technology adoption and performance efficiency. Additionally, technology adoption is found to mediate the relationship between AI technologies and performance outcomes, suggesting that the success of AI implementation depends not only on the technology itself but also on user acceptance and integration. The model demonstrates strong reliability, validity, and moderate explanatory and predictive power. These results underscore the importance of aligning technological advancements with employee readiness and adoption strategies to achieve operational excellence in high-security environments like international airports.