Artificial intelligence (AI) is advancing the field of genomics, especially when it comes to oncology. It enables the analysis and interpretation of complex molecular and clinical datasets. AI-driven tools are being used in order to predict disease outcomes, classify genetic variants and even to guide personalized treatment decisions. Integration of AI with genomic data has led to significant advancements in cancer diagnosis, prognosis and therapy selection. AI is also being widely used in rare disease research to help identify the mutations that cause them and in pharmacogenomics to ensure that treatments are tailored to each patient's unique genetic profile. This review analyzes the different uses of AI in the field of genomics in relation to oncology, pharmacogenomics and rare diseases, as well as the business AI holds for the biotechnology and pharmaceutical industries. The future of AI in genomics holds a great promise. While AI offers transformative opportunities, challenges such as data privacy, algorithm interpretability, and clinical validation must be addressed to ensure broader adoption and regulatory acceptance.