this paper provides a comprehensive study of the current state, principal challenges, and prospective directions for developing automated control and monitoring systems for open-pit transportation. The relevance of the study is underscored by the pressing need to markedly enhance the efficiency, safety, and environmental sustainability of logistics chains in coal mining enterprises amid intensifying competition and increasingly stringent production requirements. The research employs systems analysis, economic-mathematical modelling, comparative analysis, and forecasting. The scientific novelty lies in the development of an integrated criterion model for evaluating the effectiveness of automated transportation control and monitoring systems, which accounts not only for direct economic gains but also for the synergistic benefits arising from risk mitigation and improved production flexibility. This has led to the identification of technological issues such as incompatible equipment and unreliable sensors, as well as economic issues such as high capital costs and long payback periods, and organizational issues such as employee resistance and a lack of sufficient skills. Moving to intelligent automated transport management and control systems based on artificial intelligence, predictive analytics, and Internet of Things technologies is a logical future option. An economic model has been put forward that shows that the overall economic impact of implementing these types of systems is generated by preventing downtime and accidents as well as by directly saving money on repairs, fuel and lubricants. Eventually, this will significantly exceed the initial investments.