Recent discussions highlight the growing role of artificial intelligence in transforming traditionally artisanal, trial-and-error drug development into more rapid, cost-effective, and data-driven processes. Advances in AI facilitate design of gene editing therapies and allow for precision engineering of molecules, potentially streamlining and scaling therapeutic discovery. The integration promises to enhance efficiency but acknowledges that AI is not a universal solution, underscoring the need for ongoing innovation in biomedical research workflows.