Personalized medicine, also known as precision medicine, is a branch of medicine that considers each patient’s unique genetic makeup, lifestyle, and environment to customize treatment plans, preventative measures, and diagnoses. By tailoring medical interventions to individual genetic profiles, personalized medicine maximizes treatment efficacy. Better health outcomes and less trial-and-error in therapy selection result from this method, which guarantees that patients receive medicines that are most likely to work for them. Artificial intelligence-based drug discovery and design is an innovative approach that leverages artificial intelligence (AI) techniques to develop personalized medicines tailored to individual genetic profiles. AI holds immense promise in revolutionizing personalized medicine by harnessing the power of data-driven insights to optimize healthcare delivery, improve patient outcomes, and advance our understanding of disease mechanisms and treatment strategies. AI-based algorithms can be optimized to analyze large-scale, diversified datasets, including genetic information and by integrating and examining numerous data sources, AI can find patterns, correlations, and insights that conventional analytic techniques would miss. AI algorithms are used to interpret complex genomic data, such as DNA sequencing results, to identify genetic variants associated with disease susceptibility, drug response, and treatment outcomes. This chapter aims to analyze the present state of AI-based drug development for various genetic designs, along with the accompanying issues and measures to fully utilize the potential AI holds in personalized medicine.