Researchers, practitioners, and public health organizations from around the world are becoming increasingly interested in using data from consumer-grade devices such as smartphones and wearable activity trackers to measure physical activity (PA). Indeed, large-scale, easily accessible, and autonomous data collection concerning PA as well as other health behaviors is becoming ever more attractive. There are several benefits of using consumer-grade devices to collect PA data including the ability to obtain big data, retrospectively as well as prospectively, and to understand individual-level PA patterns over time and in response to natural events. However, there are challenges related to representativeness, data access, and proprietary algorithms that, at present, limit the utility of this data in understanding population-level PA. In this brief report we aim to highlight the benefits, as well as the limitations, of using existing data from smartphones and wearable activity trackers to understand large-scale PA patterns and stimulate discussion among the scientific community on what the future holds with respect to PA measurement and surveillance.