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Artificial intelligence (AI) is a significant and emerging area of research. A comprehensive analysis of the information included in the data requires the use of AI technologies, which are now more important than before at the volume and rate of data integration. In order to advance research and enhance decision-making across a wide range of professions and disciplines, including drug design, upgrading, formulation development, pharmacology, pharmacokinetics, molecular and cell biology and toxicity, AI is required for drug discovery and development. AI is crucial for enhancing growing patient population selection, patient stratification, and patient sample evaluation in clinical trials biomarkers, efficacy metrics, dose selection, and study duration). Increasing importance of AI in pharmaceutical discovery and development, as well as the rising number of start-up businesses that specialized in this area. Estimations show that the process of developing a new drug is challenging, expensive, and has a low success rate: An average of $1.3 billion is spent on R&D for each medicine. Oncology drugs take an average of 13.1 years to formulate, while non-oncology drugs take between 5.9 and 7.2 years. 13.8% of all drug-development projects complete with approval. The drug development business is attracted to AI/ML techniques because of their automated nature, predictive abilities, and an expected rise in efficiency in this review focus on role of Artificial intelligence in drug discovery and development process.