Phase 1: Requirements Definition
Document the AI workloads the infrastructure must support (training, inference, fine-tuning, or all three)
Define the scale: number of GPUs, expected utilization rate, peak vs. average load
Identify the data the infrastructure will process and where it currently resides
Define performance requirements: training throughput (tokens/second), inference latency (p99), storage throughput
Establish the timeline: when must the infrastructure be operational?
Define the operational model: internal team, managed services, or hybrid
Phase 2: Site Readiness Assessment
Assess available power capacity: how many kW are available for AI infrastructure?
Assess cooling capacity: what is the maximum rack density the current cooling system can support?
Assess structural load: can the floor support the weight of AI servers and cooling equipment?
Assess network connectivity: is there sufficient bandwidth between the AI cluster and the data sources?
Identify any site constraints that will affect the design (ceiling height, column spacing, loading dock access)
Determine whether the existing facility can support the planned deployment or whether a new facility is required
Phase 3: Compliance Requirements
Identify all applicable compliance frameworks (HIPAA, PCI DSS, FedRAMP, NERC CIP, SOX, ITAR)
Document data residency requirements: where must the data reside?
Identify audit and documentation requirements: what evidence must the infrastructure produce?
Determine whether the compliance requirements affect the architecture (e.g., air-gapped networks, HSMs)
Engage legal and compliance teams before design begins
Identify any export control requirements that affect hardware procurement
Phase 4: Procurement Planning
Identify GPU hardware lead times and initiate procurement early (currently 6–12 months for H100/H200)
Identify long-lead items: custom PDUs, liquid cooling infrastructure, network switches
Establish the procurement process: RFP, sole-source, or framework contract
Define the vendor evaluation criteria and scoring methodology
Identify any procurement constraints (approved vendor lists, budget approval thresholds)
Plan for hardware staging and receiving logistics
Phase 5: Stakeholder Alignment
Confirm executive sponsorship and budget approval
Align IT, facilities, security, and compliance teams on the project scope
Identify the project owner and decision-making authority
Establish the change control process
Define the communication plan for project status reporting
Identify dependencies on other projects or initiatives
Phase 6: Acceptance Criteria
Define GPU utilization benchmarks the system must achieve under training load
Define network throughput and latency requirements
Define storage throughput requirements
Define power and cooling performance requirements (PUE target)
Define the commissioning test plan and pass/fail criteria
Define the warranty and support terms that apply after acceptance
The most common planning failure