Abstract
<title>Abstract</title> <p>Airline operational control centers (OCCs) operate at the intersection of meteorology, aircraft performance engineering, regulatory compliance, and real-time risk management. Dispatchers and Flight Operations Officers (FOOs) are required to synthesize large volumes of heterogeneous data weather products, Notices to Airmen (NOTAMs), aircraft performance limitations, fuel burn projections, and network constraints under significant time pressure, often for dozens of flights simultaneously. This paper examines the integration of artificial intelligence (AI) and data-driven decision-support tools into airline OCC workflows, with particular attention to flight dispatch operations. Drawing on operational experience and a critical synthesis of the scholarly literature on decision support systems, predictive analytics, naturalistic decision-making, and human-AI teaming in aviation, the paper develops a conceptual framework comparing traditional and data-driven dispatch processes across eight performance dimensions: dispatch processing time, route efficiency, fuel consumption, delay reduction, dispatch decision accuracy, situational awareness, risk mitigation effectiveness, and flight completion efficiency. The analysis indicates that AI-enabled dispatch tools can meaningfully reduce flight plan preparation time, improve the consistency of fuel and route recommendations, and enhance the dispatcher's ability to detect emerging operational risk — provided that such tools are positioned as decision aids rather than autonomous decision-makers. The paper also identifies persistent challenges, including data integration complexity, algorithmic opacity, automation complacency, regulatory acceptance, and the risk of eroding the recognition-primed expertise that experienced dispatchers bring to non-routine events. The discussion concludes with industry implications for OCC design, training, and certification, and outlines a research agenda for validating AI-assisted dispatch tools under operational conditions.</p>