This systematic review explores the evolving role of artificial intelligence (AI) in addressing challenges faced by the pharmaceutical industry, focusing on supply chain disruptions, clinical trials, drug discovery, and clinical trial operations. A comprehensive literature analysis encompassed studies and developments in AI applications within the pharmaceutical sector. The review synthesizes information from various sources, including research articles, reports, and case studies. The pharmaceutical industry has encountered multifaceted challenges, including supply chain disruptions, clinical trial interruptions, and difficulties in drug development. AI emerges as a transformative solution, particularly in supply chain management, clinical trial optimization, drug discovery, and clinical trial operations. Integrating AI models, such as supervised and unsupervised learning, plays a pivotal role in predictive analytics, drug target identification, and optimization of pharmaceutical processes. The systematic review underscores the transformative impact of AI on pharmacy practice, offering innovative solutions to address challenges in the pharmaceutical industry. The findings suggest that AI applications have the potential to revolutionize supply chain management, streamline clinical trial operations, and expedite drug discovery processes. Continued research and development in AI technologies are essential for optimizing these applications and ensuring their widespread adoption in pharmacy practice.