ABSTRACT Clinical trials play a crucial role in bringing new medications, technologies, and procedures to market and into clinical practice. However, only about 10% of these studies successfully navigate the entire process from drug design through all four phases of development. This low completion rate is largely due to the increasing costs and complexities associated with conducting clinical trials. As a result, the health of the population, the standard of care, health economics, and sustainability are all adversely impacted. Artificial intelligence (AI) has the potential to streamline some of the most tedious processes in clinical trials, such as patient selection, matching, and enrollment. Improved patient selection could not only enhance the efficiency of trials but also reduce the risk of adverse treatments and their side effects. Despite its promise, the widespread adoption of AI technology in clinical trials faces several challenges and necessitates further high-quality prospective clinical validation. In this review, we explore the prospective applications of AI in clinical research and patient care, highlighting its potential to transform the landscape of clinical trials in the future.