Land subsidence, referring to the vertical sinking of land surface, is a significant geohazard posing serious risks to security of infrastructure, natural resources, built environment, and businesses in numerous places worldwide. Using deep learning approaches combined with more than 46,000 subsidence data, we predicted global land subsidence based on 23 environmental parameters. The generated global map of land subsidence covers historically documented and new subsiding areas. We estimate that more than 6.3 million square kilometers of the global land is influenced by significant subsidence rates. That includes 231,000 square kilometers of urban and dense settlement areas and a population of nearly 2 billion. The model revealed a positive correlation between the intensity of groundwater abstraction and the subsidence rate. Our results offer new insights regarding potential hotspots of land subsidence and provide the information required to devise necessary action plans and develop effective policies to mitigate this growing challenge worldwide.