Assistive Technology (AT) encompasses devices and systems that enhance functioning and independence for individuals with physical, cognitive, sensory, or developmental disabilities. With the number of AT users projected to reach 3.5 billion by 2050, these technologies are pivotal to improving quality of life. Recent advancements in rehabilitation engineering have facilitated significant strides in mobility aids, communication devices, and prosthetics. Integrating artificial intelligence (AI) into AT amplifies its impact by enabling personalized and adaptive solutions. AI-powered devices, such as orthoses that interpret user intentions or virtual environments for safe rehabilitation, offer tailored therapies and improved autonomy. In addition to its role in assistive and rehabilitation technologies, AI has revolutionized healthcare by developing Computer-Aided Diagnosis (CAD) systems. These systems leverage AI to analyze medical images, biosignals, and other patient data, aiding healthcare professionals in making informed decisions. With the advent of deep learning, CAD systems have shifted from relying on handcrafted features to automatically extracting relevant features, improving efficiency and accuracy. This chapter explores AI’s transformative potential in mobility aids, rehabilitation technologies, and CAD systems, providing an overview of classical and deep learning approaches. By enhancing diagnosis, treatment, and recovery processes, these technologies contribute to better patient outcomes and independence.