Assessment of New Competencies for Human - AI Teaming in Air Traffic Control

Artificial intelligence (AI) integration into aviation operations is progressively reshaping the professional landscape of air traffic management, thereby placing new demands on the human workforce. The aim of the study was to determine the priority weights assigned to eight specific AI competencies within the domain of air traffic control. The study was based on the framework of AI competencies applicable to the aviation sector established by the European Union Aviation Safety Agency (EASA). Data were collected from a purposive sample of 19 air traffic controllers. The data were analyzed using the Best–Worst Method (BWM), a multi-criteria decision-making technique. The findings indicate a substantial shift in the relative importance of different competencies during human-AI collaboration. Cognitive skills were assigned the highest priority weight, followed by data literacy, information technology competencies, and general AI knowledge. Communication and sensory competencies were assigned a secondary tier, while social and physical skills were allocated the lowest priority weights. These findings suggest that AI integration may transform the nature of the cognitive competencies required from air traffic controllers.