As AI moves from experimentation to large-scale deployment, infrastructure design is becoming increasingly important to overall system performance and efficiency. This session will examine how high-performance enterprise storage can support AI training, inference, and data-intensive workloads, with a focus on practical deployment considerations such as data movement, scalability, latency, and storage density. Drawing on the combined experience of DapuStor and its ecosystem partner DDN, the session will share how storage and data infrastructure can be integrated more effectively with AI compute environments to support scalable, production-ready AI infrastructure.