Assessing AI Workloads- How to Choose the Right Environment for Enterprise AI

Where should your AI workloads run? It's one of the most overlooked questions in AI strategy. From surprising constraints around power, cooling and floor space, to the growing demand for GPU-as-a-Service models, this episode delivers a field-level view of the challenges enterprises face when moving from AI proof of concept to production. You’ll hear why infrastructure readiness assessments are essential, how AI workloads differ from traditional IT, and what to consider before buying that next GPU cluster. #AIWorkloads #gpu #aiinfrastructure #datacenter #aitips #edgevscloud #glucluster #aireadiness #WWTPresents #WWT #AIProvingGroundPodcast Support for this episode provided by: Equinix https://www.wwt.com/partner/equinix/overview For more AI Proving Ground Podcasts: https://www.youtube.com/playlist?list=PLckKfxswQeZvN2YCMXjLvvSdxgpmXHzq_ For more on GPUaaS: https://www.wwt.com/article/what-is-gpu-as-a-service-gpuaas-or-gpu-cloud For more on World Wide Technology: https://www.wwt.com/ --- Chapters: 0:00 AI's Growing Power Demands 6:35 The Iron Triangle: Power, Space, Cooling 10:19 Understanding AI Workloads 16:10 Deployment Options: On-Prem, Colo, Cloud 23:26 GPU as a Service Evolution 31:09 Operational Realities and Challenges 42:28 Strategic Planning vs. Reactive Decisions 45:20 Key Takeaways and Closing Thoughts