Diseases are widespread and destructive, causing severe yield quantity and quality losses, increasing agricultural production costs, and cumulative human health and environmental risks and impacts. Climate change is anticipated to exacerbate current losses, by introducing complexity and uncertainty on our ability to adequately inform, and effectively protect, food and energy crops to ensure human populations are food, nutrition, water, and energy secure. Crop disease forecasting is advancing rapidly as precision agriculture surveillance and detection technology and Earth observation satellites are increasingly being used to automate the collection of digital agriculture 'big data'. This data is enabling artificial intelligence, predictive algorithms and models to be trained, validated, and improved for forecasting. Greater capability for conducting science in the cloud, multidisciplinary collaboration, and early warning systems are creating new opportunities and challenges for identifying, mitigating, and responding to disease outbreaks from field and farm to regional, national, and global scales.