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This publication highlights opportunities to harness geospatial data and machine learning algorithms to monitor rural roads efficiently to support connectivity. Resilient all-weather roads enable crucial access to services and economic opportunities, yet assessing and monitoring road quality can be costly and time-consuming. This publication explains how smartphones, open-source satellite imagery, and artificial intelligence can be used to augment traditional surveys to improve road data in cost-effective and efficient ways. It draws on a study developed in collaboration with the World Data Lab and the governments of the Philippines and Thailand, supported by the Japan Fund for Prosperous and Resilient Asia and the Pacific.