Artificial Intelligence (AI) is playing a transformative role in drug development, offering significant potential to accelerate the traditionally slow and expensive process. This review examines the integration of AI into key stages of drug discovery, such as target identification, compound screening, clinical trials, and personalized medicine. By reviewing recent advancements, the review highlights the strengths of AI in speeding up drug development, while also addressing the challenges such as data quality, model interpretability, and regulatory issues that still need to be overcome.