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We examine how generative AI techniques are revolutionizing the discovery, design, property prediction, and optimization of biomaterials across multiple scales and applications, particularly in tissue engineering, regenerative medicine, and drug discovery. Furthermore, we discuss the synergies between generative AI and other cutting-edge technologies, such as high-throughput 3-dimensional bioprinting, highlighting how these integrations are accelerating progress in the field. We also address the challenges and limitations of applying generative AI to biomateriomics, including issues related to data quality and availability, model interpretability, validation of AI-generated designs, and ethical considerations. Looking forward, future advancements, including multimodal AI systems and quantum\u2013AI hybrids, promise to further expand the potential of biomateriomics, fostering innovation in sustainable materials, personalized medicine, and environmental applications. 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