In recent years artificial intelligence (AI) has become one of the most influential technologies in biological and medical sciences, particularly in the field of genomic research, which focuses on studying and analyzing the genetic material of living organisms. With the rapid advancement of DNA sequencing technologies, scientists can now generate enormous amounts of genetic data in a relatively short period of time. This has created a growing need for advanced computational tools capable of processing and interpreting these complex datasets efficiently. Artificial intelligence has emerged as a powerful solution for managing and analyzing genomic information, enabling researchers to gain valuable insights that were previously difficult or impossible to obtain. AI applications in genomics rely on machine learning and deep learning algorithms that can identify complex patterns and relationships between genes and inherited traits. These technologies help researchers discover genes associated with genetic disorders and chronic diseases such as cancer, diabetes, and cardiovascular diseases. AI also plays a critical role in detecting genetic mutations and predicting their potential impact on cellular functions, which contributes to earlier and more accurate disease diagnosis. Furthermore, AI is widely used in gene expression studies, allowing scientists to understand how genes are activated or suppressed under different biological conditions. This knowledge improves our understanding of disease mechanisms at the molecular level. Another important application of AI is in drug discovery and development, where it can predict interactions among genes, proteins, and pharmaceutical compounds, significantly reducing the time, cost, and effort required in traditional research processes. In addition, AI supports the advancement of personalized medicine, which aims to design treatment strategies based on an individual's unique genetic profile, thereby increasing treatment effectiveness and minimizing adverse side effects. Despite its many advantages, the use of AI in genomics faces several challenges, including data privacy concerns, the need for accurate predictive models, and the availability of reliable and diverse genomic databases. Researchers continue to work on improving these technologies to ensure their safety and effectiveness. Looking ahead, the integration of artificial intelligence and genomics is expected to revolutionize healthcare by enhancing disease prevention, diagnosis, and treatment while providing deeper insights into the human genome and its role in health and disease.