This chapter examines the transformative role of AI-driven digital technologies in supporting care-dependent older adults living at home, with a focus on fall detection, prevention, and functional mobility promotion. It highlights how wearable and ambient sensors, combined with AI methods, can monitor mobility, predict fall risk, and detect falls in real time—enabling early intervention, promoting independence, and reducing caregiver burden. Drawing on current research and practical use cases, the chapter explores key implementation requirements and addresses challenges such as digital inequity, user acceptance, data privacy, and ethical concerns. Emphasizing participatory design and scalable solutions, it advocates for inclusive, user-centered approaches that align technological innovation with the lived realities of older adults and caregivers.