There is a major transformation happening in the world of medical rehabilitation, catalyzed by the integration of emerging technologies like artificial intelligence, robotics, and biosensor systems. Specifically, exoskeletons—that augment human physical abilities designed as wearable robotic units—play an incrementally pivotal role in rehabilitation and therapy. However, it’s just the beginning; we’re early on to understand the potential of these devices. We envision that personalized care in rehabilitation medicine can be revolutionized by incorporating artificial intelligence into these robotic frameworks. For patients with varying disabilities, exoskeletons are proving to be effective in providing basic mobility assistance. There’s little proven methodology about their efficacy in delivering comprehensive, adaptable rehabilitation programs. This paper discusses the potential of integrating advanced AI into modern exoskeletons that can have the potential to enhance the quality and adaptiveness of physiotherapy. The core value of this intervention is to truly bring about personalization in treatment plans. Leveraging machine learning, the data garnered from patient-machine interactions can be leveraged to infer strength, mobility range, and therapy response in real time. This data-driven approach evolves in real-time ensuring the treatment is relative to patient progress, thus enabling a personalized, adaptive rehabilitation. Our research study discusses how such adaptive algorithms can supplement exoskeletons’ learning ability and rehabilitative process.