Background <p>Green organic synthesis has emerged as an area of interest in drug discovery research because of the environmental, regulatory, and economic challenges associated with traditional synthetic methods.</p> Problem <p>Despite the availability of green chemistry solutions, pharmaceutical synthesis is still limited to empirical optimization and trial-and-error approaches.</p> Approach <p>Recent advances in artificial intelligence and quantum chemistry are now making it possible to predict outcomes in reaction design, retrosynthesis, catalyst design, and reaction mechanisms. Artificial intelligence can facilitate data-driven prediction and optimization, while quantum chemistry can provide insights into mechanism details and selectivity.</p> Key advances <p>This review highlights recent advances in combining AI with quantum chemistry to further green organic synthesis in reaction prediction, catalyst and solvent optimization, and drug-related examples.</p> Outlook <p>These approaches are on the cusp of enabling more efficient, selective, and environmentally benign synthetic methodologies for sustainable drug discovery.</p> Graphical abstract <p></p>