The advent of Artificial Intelligence (AI) is ushering in a new era across scientific disciplines, with chemistry being one of the most profoundly impacted. This review article explores the multifaceted integration of AI, particularly machine learning (ML) and deep learning (DL), into various branches of chemistry, including drug discovery, materials science, chemical synthesis, and analytical chemistry. We delve into how AI is accelerating the pace of discovery, optimizing processes, and enabling novel insights that were previously unattainable through traditional experimental or computational methods. Furthermore, this article discusses the current methodologies, highlights significant results and breakthroughs, and addresses the prevailing challenges and future prospects of AI in revolutionizing chemical research and industrial applications. The ethical implications and the need for explainable AI (XAI) in chemistry are also critically examined.
Yadav et al. (Mon,) studied this question.