Technology continues to develop, we see that developments are increasingly adopting the evolution of artificial intelligence (AI), thereby triggering unprecedented progress in various fields, especially in medical science. This paper raises the issue of antimicrobials and researchers investigating this field have many problems that arise in people’s lives. Therefore, it is necessary to utilize generative artificial intelligence to carry out cognitive acquisition. Researchers believe that using generative AI, especially in the form of a generative adversarial network (GAN) and using a deep learning architecture, will provide extraordinary benefits in understanding the complex dynamics of AMR tools. Through extensive data synthesis and aggregation, GANs can facilitate the acquisition of new insights into microbial behavior, evolution of resistance mechanisms, and prediction of antimicrobial efficacy. Additionally, the perceived utility of implementing generative AI in cognitive acquisition has been proven to be effective as there are already several researchers who have implemented it and succeeded. This research simulates various scenarios of previous researchers and also optimizes treatment through an AI-based approach offering an unprecedented opportunity to combat the serious challenges posed by antimicrobial resistance. This collaboration to build AI is critical to cognitive advances in medical science. In conclusion, the use of generative artificial intelligence in the field of medical science, especially in overcoming antimicrobial resistance, has enormous potential. By absorbing lessons from AMR leaders, we are paving the way for innovative approaches to combat this global health crisis and advance medical research. It is hoped that readers and other stakeholders can support this innovation.