AI Enhanced Organic Chemistry: Emerging Tools and Computational Strategies

Abstract

Artificial intelligence (AI) is transforming organic chemistry by making it possible to make predictive and data-driven contributions to the design of molecules, synthesis of molecules, and optimization of reactions. Machine learning, deep learning and cheminformatics AI applications are used to predict reactions, plan retrosynthetic, and analyze computations, and save time and resources on experimentation. New instruments and platforms combine AI and automation, high-throughput experimentation and molecular modeling, which is speeding up the discovery in pharmaceuticals, materials and green chemistry. Even though some of the challenges to AI have been the data quality, interpretability, and experimental translation, the opportunities that AI presents are enormous and unexplored. This review also mentions existing applications, case studies, computational strategies, and future views and demonstrates the transformative influence of AI in the field of modern organic chemistry.