This review examined the role of artificial intelligence (AI) in stroke rehabilitation across different phases of recovery, from early diagnosis to long-term recovery. The researchers analyzed multiple studies in acute care, subacute, and long-term rehabilitation, highlighting AI applications such as robotic-assisted therapy, virtual reality-based interventions, and predictive modeling of patient outcomes. These technologies were often used in addition to conventional rehabilitation methods, including physical and occupational therapy, over periods ranging from days to several months. Key factors that were assessed included motor recovery, functional independence, cognitive improvement, and quality of life. The review suggested that AI interventions overall enhanced motor function, improved task-specific performance, and supported the development of individualized treatment plans. This demonstrates how AI is promising in aiding traditional rehabilitation strategies. However, differences in study design, sample size, and AI modalities highlight the need for a standardized protocol to optimize its use in the clinical setting.