Meeting the Challenges of Operating Infrastructure in the AI Era
White Papers
An Omdia white paper on what it takes to run AI factories, from GPU complexity to IT and OT convergence.
AI factories are changing how data centers are built and run. New hardware, higher power densities, and mixed legacy and cutting-edge environments demand skills and processes many IT teams don’t have yet. This Omdia white paper, commissioned by Park Place Technologies, explains what’s changing and how CIOs can prepare their operations for it.
What you’ll learn
- Why a hybrid model is gaining traction and what it means for managing AI workloads
- The top challenges mid-market CIOs face when adopting AI factories
- How GPUs strain power, cooling, networking, storage, and skills
- Why IT and OT teams need shared data to predict failures before they happen
- How one AI-focused university gained device-level visibility across a mixed GPU and CPU environment
Key stats
- 33% of mid-market customers name technical complexity as their top AI adoption challenge
- 40 to 100 kW per rack in AI factories, compared with 5 to 10 kW in standard enterprise racks
- 65% of organizations plan to adopt sovereign environments for AI workloads in 2026 to 2027
Who it’s for
CIOs, IT infrastructure leaders, and data center operations teams planning for or already running AI workloads.