This article discusses the application of artificial intelligence (AI) in the design, optimization, and biomedical applications of hydrogels. Traditional hydrogel design methods are time-consuming and expensive, but AI has introduced a revolutionary breakthrough in materials science by enabling efficient design and optimization. AI can predict and optimize hydrogel properties, perform multi-attribute optimization, and facilitate high-throughput screening and automated material discovery. These capabilities significantly enhance the efficiency and effectiveness of hydrogel development. Hydrogels, due to their high water content and similarity to natural tissues, have found broad applications in drug delivery, tissue engineering, wound dressing, and biosensors. However, the development of hydrogels faces challenges such as complex design processes, time-consuming optimization, and long application cycles. AI can address these challenges by providing predictive models, optimizing experimental design, and improving performance monitoring. AI technology is particularly valuable in hydrogel design and biomedical applications. For example, AI can predict hydrogel composition and properties, optimize formulations for drug delivery systems, and enhance the performance of biosensors. In drug delivery, AI can predict drug release profiles, optimize drug loading, and monitor drug release in real-time. In tissue engineering, AI can assist in designing hydrogels with specific properties for tissue repair and regeneration. In 3D printing, AI can enhance the printability of hydrogels by predicting and optimizing their properties, enabling the development of bio-inks for advanced manufacturing. AI also plays a crucial role in the development of multifunctional hydrogels for wound dressings, which can provide real-time monitoring and personalized treatment. Overall, AI has the potential to significantly advance the design and application of hydrogels in biomedicine. By leveraging AI techniques, researchers can develop more efficient, effective, and innovative hydrogel materials for various biomedical applications. Despite the current challenges, the integration of AI in hydrogel research is expected to lead to significant advancements in the field.This article discusses the application of artificial intelligence (AI) in the design, optimization, and biomedical applications of hydrogels. Traditional hydrogel design methods are time-consuming and expensive, but AI has introduced a revolutionary breakthrough in materials science by enabling efficient design and optimization. AI can predict and optimize hydrogel properties, perform multi-attribute optimization, and facilitate high-throughput screening and automated material discovery. These capabilities significantly enhance the efficiency and effectiveness of hydrogel development. Hydrogels, due to their high water content and similarity to natural tissues, have found broad applications in drug delivery, tissue engineering, wound dressing, and biosensors. However, the development of hydrogels faces challenges such as complex design processes, time-consuming optimization, and long application cycles. AI can address these challenges by providing predictive models, optimizing experimental design, and improving performance monitoring. AI technology is particularly valuable in hydrogel design and biomedical applications. For example, AI can predict hydrogel composition and properties, optimize formulations for drug delivery systems, and enhance the performance of biosensors. In drug delivery, AI can predict drug release profiles, optimize drug loading, and monitor drug release in real-time. In tissue engineering, AI can assist in designing hydrogels with specific properties for tissue repair and regeneration. In 3D printing, AI can enhance the printability of hydrogels by predicting and optimizing their properties, enabling the development of bio-inks for advanced manufacturing. AI also plays a crucial role in the development of multifunctional hydrogels for wound dressings, which can provide real-time monitoring and personalized treatment. Overall, AI has the potential to significantly advance the design and application of hydrogels in biomedicine. By leveraging AI techniques, researchers can develop more efficient, effective, and innovative hydrogel materials for various biomedical applications. Despite the current challenges, the integration of AI in hydrogel research is expected to lead to significant advancements in the field.