Artificial intelligence (AI) and machine learning (ML) are altering drug discovery by accelerated and improving certain phases of the research process. Drug discovery has historically been time-consuming and expensive, but AI and ML have made the process quicker by evaluating huge historical data, identifying drug-target interactions, and improving molecular designs with more quality. Machine learning algorithms use virtual screening to find viable drug candidates, minimizing the demand for expensive laboratory testing. AI-driven technologies such as Alpha Fold have made improvements in protein structure prediction, allowing for more accurate targeting and speedier medication development. Furthermore, natural language processing (NLP) algorithms examine scientific research to provide information. Future directions involve the use of AI and quantum technology to improve molecular simulations and improve precision medicine by personalizing therapies to specific genetic profiles. Furthermore, AI will be critical in refining clinical trial designs, predicting patient responses, and providing the safety of medicines, resulting in quicker time to market and improved patient outcomes. As AI and machine learning techniques progress, their impact on drug discovery is projected to increase, revolutionizing the pharmaceutical sector.