Polygenic scores (PGS) are increasingly being used in clinical settings to stratify risk and guide diagnostic pathways, predict therapeutic responses, and enhance the efficiency of clinical trials. PGS can complement traditional risk factors, such as demographics and family history, to provide additional information about an individual's genetic predisposition to diseases. However, several challenges must be addressed to maximize the clinical utility of PGS, including ensuring FAIR (Findable, Accessible, Interoperable, and Reusable) use, equitable performance across populations, robust and reproducible calculations, and responsible communication and interpretation of results. The review highlights the potential benefits of PGS, such as improving risk prediction, guiding treatment decisions, and enhancing diagnostic accuracy. It also discusses the analytical challenges and solutions, emphasizing the need for diverse and multi-ancestry data to improve transferability and accuracy. The authors advocate for open sharing of genomic data and developed PGS according to FAIR principles and established reporting guidelines. They also stress the importance of responsible use, communication, and interpretation of PGS results to avoid genetic determinism and exceptionalism. The review concludes by emphasizing the ongoing progress in PGS development and the need for further translational studies, including pragmatic trials, to provide empirical evidence of PGS utility in specific clinical scenarios. It calls for community efforts to ensure equitable access to PGS benefits, particularly in underrepresented groups, and to promote ethical partnerships for data collection and analysis.Polygenic scores (PGS) are increasingly being used in clinical settings to stratify risk and guide diagnostic pathways, predict therapeutic responses, and enhance the efficiency of clinical trials. PGS can complement traditional risk factors, such as demographics and family history, to provide additional information about an individual's genetic predisposition to diseases. However, several challenges must be addressed to maximize the clinical utility of PGS, including ensuring FAIR (Findable, Accessible, Interoperable, and Reusable) use, equitable performance across populations, robust and reproducible calculations, and responsible communication and interpretation of results. The review highlights the potential benefits of PGS, such as improving risk prediction, guiding treatment decisions, and enhancing diagnostic accuracy. It also discusses the analytical challenges and solutions, emphasizing the need for diverse and multi-ancestry data to improve transferability and accuracy. The authors advocate for open sharing of genomic data and developed PGS according to FAIR principles and established reporting guidelines. They also stress the importance of responsible use, communication, and interpretation of PGS results to avoid genetic determinism and exceptionalism. The review concludes by emphasizing the ongoing progress in PGS development and the need for further translational studies, including pragmatic trials, to provide empirical evidence of PGS utility in specific clinical scenarios. It calls for community efforts to ensure equitable access to PGS benefits, particularly in underrepresented groups, and to promote ethical partnerships for data collection and analysis.