OPTIMIZING ECONOMIC EFFICIENCY IN MODERN TRANSPORT SYSTEMS THROUGH ARTIFICIAL INTELLIGENCE-DRIVEN OPERATIONAL MANAGEMENT

Abstract

In the face of rising operational costs, volatile energy prices, and fluctuating
passenger demand, modern transport systems—particularly high-speed rail and
urban logistics—require advanced management solutions to ensure financial
sustainability. This paper investigates how the integration of Artificial Intelligence
(AI) and Big Data analytics can optimize the economic efficiency of transport
operations. By shifting from traditional, reactive management models to data-driven,
proactive systems, transport enterprises can significantly reduce waste and
maximize revenue