Clinical trials are essential for assessing the safety and efficacy of new treatments and securing regulatory approvals. However, they are resource-intensive and often hindered by inefficiencies in protocol design, participant recruitment, and data management. This chapter explores how advancements in artificial intelligence (AI), particularly in large language models (LLMs), are transforming these processes. AI-powered tools streamline protocol drafting, improve eligibility criteria, address missing data issues, and enhance safety assessments. Innovations such as conversational AI for patient interaction, federated learning for secure and decentralized data analysis, and standardized metadata frameworks have advanced patient-centred methodologies and pharmacovigilance practices. These technologies provide real-time insights, broaden participant engagement and demographic diversity, and improve the generalizability of trial outcomes, while reducing costs and accelerating timelines. By examining the role of AI across the clinical trial lifecycle, this chapter highlights its current applications, innovative methodologies, and transformative future potential to create more efficient, inclusive, and impactful clinical research processes.