In this comprehensive guide, we will explore the key factors to consider when selecting an AI server setup, including understanding your AI workload requirements, determining the right hardware configuration, choosing the right operating system, selecting the right storage. In this comprehensive guide, we will explore the key factors to consider when selecting an AI server setup, including understanding your AI workload requirements, determining the right hardware configuration, choosing the right operating system, selecting the right storage. The preferred approach is to start your AI adoption with Azure AI platform-as-a-service (PaaS) solutions. However, if you have access to Azure GPUs, follow this guidance to run AI workloads on Azure IaaS. AI workloads require specialized virtual machines (VMs) to handle high computational demands. Ensure optimal performance, scalability, and reliability for seamless development and deployment. We'll give you a 2 week free trial of Inbox Placement Optimizer, so you can see results first hand. No work required from your end. You need. Local deployment offers faster iteration, lower latency, full control, predictable costs, and secure data. GPU: NVIDIA RTX PRO Blackwell (96 GB VRAM, 5th-gen Tensor Cores) for training/inference; rack-ready for 2U–4U servers.