This chapter introduces artificial intelligence (AI) algorithms and their transformative applications in virology research. It provides a comprehensive overview of various AI techniques, including regression analysis, support vector machines (SVMs), k-nearest neighbors (kNNs), clustering methods, decision trees, random forests, and advanced neural networks such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). These algorithms are essential for tasks like data analysis, prediction, classification, and pattern recognition. The chapter further explores the role of AI in virology, focusing on its applications in virus classification, antiviral drug development, vaccine discovery, diagnostic advancements, and predictive modeling for epidemics. Personalized medicine and treatment optimization are also discussed. A case study demonstrates the use of machine learning models to study the protein determinants influencing host-specific infection patterns in polyomaviruses. In conclusion, the chapter emphasizes the growing impact of AI in virology and highlights the potential for future advancements to shape research and therapeutic approaches.