The COVID crisis has accelerated the integration of artificial intelligence (AI) in drug discovery and omics research, providing novel avenues to tackle intricate issues in virology research. AI has lately enabled significant breakthroughs in a wide range of biological disciplines, including genetic variant interpretation, protein structure prediction, disease detection, and pharmaceutical creation. It has prominently assumed a pivotal role in virology research, with generative AI at the forefront of innovation. Generative AI (GAI) is a subset of AI that majorly focuses on creating new data or content resembling existing data through learning underlying patterns and relationships. It has revolutionized virology/omics study by generating synthetic data to augment limited datasets, predicting protein structures, identifying gene regulatory networks, and assisting in drug discovery through virtual screening, accelerating advancements in genomics, proteomics, and metabolomics research. This chapter aims to discuss the basic concept of generative models and their current and future scope in virology.