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Conceptual analysis reveals the potential of unified artificial intelligence in airport operations, suggesting proactive risk detection improves aviation safety.
Artificial intelligence is emerging as a potential new layer of airport Safety Management Systems by integrating operational, environmental, infrastructure, personnel, and surveillance data into a continuously updated assessment of airport risk. Rather than treating runway incursions, foreign object debris, wildlife hazards, pavement degradation, weather, staffing, fatigue, emergency response, construction, maintenance, and ground movement as isolated safety domains, the intelligent airport concept combines them to identify hazardous interactions that may remain invisible within traditional departmental structures. Current advances in machine learning, computer vision, surface surveillance, predictive maintenance, digital twins, and human-AI decision support demonstrate that many of the technological components already exist, while manufacturers, the Federal Aviation Administration, military organizations, and research institutions are progressively developing related capabilities. However, the transition from fragmented AI applications to an integrated airport-wide safety intelligence layer introduces substantial challenges involving explainability, certification, cybersecurity, privacy, employee monitoring, legal liability, public-sector governance, and human authority. This article argues that the most effective future model is not an airport controlled by artificial intelligence, but an airport whose Safety Management System is augmented by AI capable of continuously recognizing combinations of weak safety signals before they converge into an accident sequence. Such an architecture could transform airport safety from primarily reactive and periodically predictive risk management into persistent, system-wide anticipatory awareness.
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A. F. Clark (2026) studied this question.
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