This chapter explores the future directions and emerging opportunities in genomicGenomics artificial intelligence (AIArtificial Intelligence (AI)). ​ It highlights advancements in genomic foundation modelsGenomic foundation models, including the development of architectures that address the unique biophysical properties of the genome, such as its extreme length, symmetry, and regulatory logic. Key innovations include breaking the quadratic barrier in context length, enforcing biological equivariance, and adopting advanced tokenization strategiesTokenization strategies. The chapter also delves into generative biologyGenerative biology, showcasing models capable of designing novel molecular systems and regulatory architecturesRegulatory architectures. The concept of AIArtificial Intelligence (AI)-driven digital twinsDigital twins is introduced, enabling predictive modeling of biological systems and personalized medicine. Furthermore, the integration of multi-omicsMulti-omics data, real-time edge genomicsEdge genomics, and autonomous scienceAutonomous science through self-driving labs is discussed. ​ The chapter concludes with an exploration of ethical, biosecurityBiosecurity, and governance challenges posed by these transformative technologies, emphasizing the need for proactive measures to ensure safe and secure development. ​