Enterprises Shift AI Workloads To Private Clouds Over Data Sovereignty, Token Costs, And Control Concerns
SiliconANGLE, Monday, August 31st, 2026
From Private Cloud to Private AI Cloud, Software Decides Who Wins
Enterprise cloud AI deployments are moving toward privately owned infrastructure as organizations grapple with data sovereignty, tokenomics, and operational costs.
Chris Wolf, global head of AI and advanced services at Broadcom's VMware Cloud Foundation Division, emphasizes that IT operations teams must now balance frontier models, specialized models, and agentic workloads on shared hardware.
Wolf warns against buying hardware first and deciding software later, arguing that software flexibility determines accelerator choice and model deployment options.
Sovereignty requirements from governments in North America, Europe, and Asia are driving localized models and encryption controls. Enterprises must architect for change and prioritize software strategy before infrastructure.