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Early warning of landslides is crucial for risk management and reduction, attracting a lot of attention from both scientists and stakeholders. However, it is challenging due to the complex nature of landslide behaviors and failure mechanisms. Here, we present a recent case of successful early warning and timely evacuation in advance of a large rockslide that occurred on 17 February 2019, in Guizhou Province, China. The rockslide was initially triggered in 2014 due to the excavation of slope toe for road expansion. Since then, the rockslide had become a potential threat to the local residents, pedestrians, and traffic. To ensure their safety, a wireless monitoring network combining on-site sensors and the geodetic method by Global Navigation Satellite System (GNSS) was installed to continuously monitor the surface displacement of the rockslide. Field monitoring data measured by crack gauges, rain gauges, and tiltmeter were transmitted to a real-time early warning system developed using the new artificial intelligence by the authors' institute. Since the deformation of the rock mass was found increasing, nearby residents were evacuated immediately. Using predefined early warning thresholds for rockslides in the system, the rockslide was successfully forecasted 53 min in advance. Prompt action taken by scientists and local authorities averted human and economic losses completely. In this study, we introduce the real-time early warning system, its concept, the method for determining warning threshold, and performance, followed by the emergency mitigation measures performed for this particular rockslide. It is the 5th time our early warning system successfully forecasted a landslide since its implementation in 2017, and hence we discuss the key characteristics of the system in order to make it applicable for other cases globally. [ABSTRACT FROM AUTHOR]