2026 Event Schedule

Enterprises are being challenged in data center capacity and capability planning across each of on-premises, colocation, and cloud delivery models for both traditional corporate processing needs and rapidly growing artificial intelligence initiatives.

Many end users are finding that their existing data centers cannot accommodate anticipated AI development and rollout programs, and new data center construction is very expensive. Rapidly evolving AI training models and subsequent inference applications have significantly complicated the planning process when C-level executives want to see effective and affordable data center capacity and capability plans that can be flexibly adjusted over time as AI deployment lessons are learned.

This session will discuss the process for quantifying and evaluating needs for AI readiness, reliability, scalability, electricity delivery, cooling (densities and methods), telecom bandwidth, network latency, cloud migration, cloud proximity, audit/compliance, sustainability, hazards/risks, security, provider competency, contract flexibility, reducing operating costs, and controlling capital expenditures to properly plan for future data center requirements.

This fast-paced interactive session will present several case study summaries and a planning framework for enterprise use creating cost-effective data center capacity and capability plans that are customizable for each organization's specific needs.