Background: Cerebral palsy is a complex neurodevelopmental disorder with various etiological factors and treatment options. This narrative review aimed to summarize the causes of cerebral palsy, identify areas needing additional research in treatment approaches, and highlight areas requiring further investigation. In order to provide a thorough overview of management techniques to lessen the effects of the illness and its consequences, this review has drawn data from a number of studies. Introduction: Prematurity increases the risk of brain damage during the developing stage and accounts for a sizable fraction of cerebral palsy cases. In a sizable portion of cases, maternal diabetes and hypertension are listed as the main causes. Damage to the brain tissue results from hypoxic-ischemic injuries sustained during pregnancy that upset the equilibrium of oxidants and antioxidants. To alter the oxidative stress pathway and ease related issues, pharmacological treatments, such as therapeutic hypothermia, free radical inhibition therapy, and mitochondrial therapy, have been proposed. Therapeutic strategies, such as physiotherapy, occupational therapy, speech therapy, and surgical interventions, have added quality to the lives of the children. Some of the most recent developments in this area include the development of biomarkers for muscle activity detection, machine learning to predict the types of cerebral palsy and abnormal movements, disease prediction with eye images, wireless inertia measuring unit for spasticity detection, computerbased video analysis of typical and atypical infants, identification of intellectual disabilities with algorithms, and deep learning methods for predicting cerebral palsy. Methods: This narrative review is based on a careful analysis of numerous researches conducted on cerebral palsy, which have served as the basis for statistical distribution. It reviews the causes of cerebral palsy, available treatments, and ongoing research with the goal of providing physicians and researchers in the field with useful information. The objectives, study questions, inclusion criteria, and search approach have all been outlined in a thorough protocol. To find pertinent research published up to September 2021, a literature search was carried out using electronic databases, including Google Scholar, PubMed, Cochrane Library, Scopus, and Web of Science. A combination of pertinent keywords, such as "cerebral palsy," "management," "technology," "wearable technology," "prematurity," and "artificial intelligence," has been used in the search approach. Results: Recent advances in the field include the discovery of biomarkers for the detection of muscle activity, machine learning algorithms to predict the types of cerebral palsy and abnormal movements, disease prediction using eye images, wireless inertia measuring units for the detection of spasticity, computer-based video analysis for the detection of atypical infants, and algorithms to identify intellectual disabilities. Additionally, employing technologies, like virtual reality systems, electrical stimulators, activity trackers, machine learning, and deep learning approaches, has shown promise in evaluating, diagnosing, and predicting treatment outcomes linked to gait, upper limb, and lower limb function. Conclusion: Future research should examine the clinical application of nanomedicine, stem cell therapy, and cutting-edge therapeutic strategies to prevent hypoxic-ischemic damage in the developing brain. Additionally, research is required to effectively assist children with severe speech difficulties using alternate communication modalities and cutting-edge computational tools. The outcomes for people with cerebral palsy can be improved by combining interdisciplinary efforts with cutting-edge technological interventions.