A major challenge in drought monitoring and prediction is translating research advances into reliable, large-scale operational systems that support situational awareness and decision-making. Operational drought services are increasingly critical as drought events become more frequent and prolonged, requiring early action before impacts cascade across water resources, agriculture, ecosystems, and public services. This session focuses on advances in the development, implementation, and evaluation of regional- to continental-scale drought monitoring and prediction systems designed for operational use. Emphasis is placed on the integration of multi-source observations, real-time data streams, and artificial intelligence approaches to improve subseasonal-to-seasonal predictability, identify operational drought thresholds, and enhance real-time monitoring, particularly in the context of regional drought challenges and evolving operational needs. Examples from recent studies and operational systems highlight effective pathways for transitioning research into practice, including collaborations among research institutions, operational agencies, and stakeholders. Contributions reflecting these efforts are encouraged.