Artificial Intelligence (AI) has come a long way in healthcare, having played significant roles in data and information storage and management—such as in patients' medical histories, medicine stocks, sale records, and so on; automated machines; and software and computer applications like diagnostic tools, including MRI radiation technology, CT diagnosis, and many more—all of which have been created to facilitate and simplify healthcare measures. Without a doubt, artificial intelligence (AI) has transformed healthcare over the past few decades to become more effective and efficient, and the pharmaceutical industry is not an exception. AI has had several implications for the pharmaceutical industry. The first sector is Drug Development and Discovery: businesses such as Atomwise accelerate the early phases of drug discovery by using AI for virtual screening, which predicts the behavior of various compounds. The second sector is clinical studies; by identifying suitable participants, forecasting results, and continuously monitoring patient data, artificial intelligence (AI) assists in the design of more effective clinical studies. AI is used, for instance, by IBM Watson Health to match patients with suitable clinical trials by analyzing patient data. The third sector is personalized medicines; AI is used in personalized medicine to customize care based on each patient’s unique genetic profile. Businesses like Tempus help doctors tailor cancer treatment regimens by using AI to evaluate clinical and molecular data. The fourth sector is Supply Chain Management; AI makes the supply chain more efficient by forecasting demand, controlling inventories, and guaranteeing that medications are delivered on time. This lowers expenses and boosts productivity in the pharmaceutical sector. This analysis highlights the advantages and disadvantages of the many AI-based techniques used in pharmaceutical technology.