Artificial intelligence (AI) is being used to improve clinical trials, which are time-consuming and expensive. AI can help with trial design, patient recruitment, data analysis, and patient retention. For example, AI can predict the success of a trial, help find eligible patients, and reduce the number of patients needed for a trial. AI can also help with patient retention by predicting who is likely to drop out and intervening. AI can also help with data management, such as extracting data from unstructured reports and annotating images or lab results. AI can also help with trial reporting, such as preparing reports for the FDA. However, there are ethical and practical challenges to AI's deployment in clinical trials, such as bias in AI models and the need for large amounts of training data. Despite these challenges, AI has the potential to revolutionize clinical trials by making them more efficient and effective. The use of AI in clinical trials is increasing, with companies developing AI-powered tools to help with various aspects of clinical trials. The FDA has relaxed some of its regulations in recent years, leading to increased innovation in clinical trials. The use of AI in clinical trials is expected to continue to grow, with more companies developing AI-powered tools to help with various aspects of clinical trials.Artificial intelligence (AI) is being used to improve clinical trials, which are time-consuming and expensive. AI can help with trial design, patient recruitment, data analysis, and patient retention. For example, AI can predict the success of a trial, help find eligible patients, and reduce the number of patients needed for a trial. AI can also help with patient retention by predicting who is likely to drop out and intervening. AI can also help with data management, such as extracting data from unstructured reports and annotating images or lab results. AI can also help with trial reporting, such as preparing reports for the FDA. However, there are ethical and practical challenges to AI's deployment in clinical trials, such as bias in AI models and the need for large amounts of training data. Despite these challenges, AI has the potential to revolutionize clinical trials by making them more efficient and effective. The use of AI in clinical trials is increasing, with companies developing AI-powered tools to help with various aspects of clinical trials. The FDA has relaxed some of its regulations in recent years, leading to increased innovation in clinical trials. The use of AI in clinical trials is expected to continue to grow, with more companies developing AI-powered tools to help with various aspects of clinical trials.