Diabetic foot ulcers have a major health and economic cost, frequently leading to hospitalization, amputation, and impacting quality of life. Prevention and early detection of diabetic foot ulcers are key to enabling an improved outlook for this common complication of diabetes. Intelligent insole technology measuring and feeding-back pressure information to the patient on a daily basis has been shown to reduce the incidence of diabetic foot ulcers in high-risk diabetes patients. Timely and frequent pressure “alerts” support offloading adherence. Computer vision techniques involving machine learning can develop models capable of automatically detecting diabetic foot ulcers from foot images. Automatic recognition of foot ulcers improves screening and early detection and is further advanced through developments in cloud computing, which mean that this “artificial intelligence” technology can be employed in any location, not limited by mobile device capabilities. These novel technologies present opportunity for changing the future outlook of diabetic foot care.