You can buy the GPUs but that doesn't mean you can run them. Across the enterprise, AI investment is accelerating but the infrastructure behind it is lagging further than most teams realize. Power ceilings are being hit. Cooling systems are stretched. Floor space and rack density are becoming real constraints. And in many cases, organizations are discovering these limits after the hardware shows up.

In this episode of WWT Presents Research, host Robb Boyd and Corey Wanless, a principal solutions architect, explore ways in which organizations can automate infrastructure and processes for AI success.

Private cloud sounds simple until you sit in the room where the decisions get made. Everyone agrees they want it — but everyone means something different. That's where things start to drift. Teams buy hardware, timelines get tight, and suddenly the foundation is poured before anyone agrees on what the cloud is supposed to deliver.

Many organizations move to the cloud expecting speed and savings, only to end up with ballooning bills, siloed teams and mounting frustration. In this episode of WWT Presents Research, Robb Boyd talks with Jeff Weeks, creator of WWT's Cloud Operating Model framework and Michelle Dupuis, one of only 300 certified FinOps professionals worldwide, to unpack why the problem isn't the cloud but how you're running it. Learn why fixing your operating model is the foundation for securing data, enabling AI infrastructure and modernizing legacy applications. Cloud success is not just about migration; it is about mastering the model that makes it work.