RationalePre-eclampsia, a severe hypertensive disorder of pregnancy, poses significant maternal and perinatal risks. Artificial intelligence (AI) offers the potential for improved prediction, risk stratification, and personalized management. This umbrella review aims to synthesize existing systematic reviews to evaluate AI’s current applications, benefits, limitations, and ethical considerations in pre-eclampsia care. MethodsThis umbrella review will follow the Joanna Briggs Institute (JBI) methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We will systematically search major databases for relevant systematic reviews that examine the application of AI in pre-eclampsia. Data extraction will include information on AI algorithm performance, clinical applications, predictive variables, population diversity, ethical considerations, and limitations. Quantitative and qualitative synthesis of the extracted data will be performed to address the specific aims. Discussion This review’s findings will critically examine AI’s translational potential in pre-eclampsia care. We will discuss the balance between the promise of enhanced predictive accuracy and the practical challenges of clinical implementation, including data quality, model interpretability, and the need for rigorous validation across diverse populations. Ultimately, this review will contribute to a nuanced understanding of how AI can be responsibly leveraged to improve maternal and perinatal outcomes in pre-eclampsia.