Why GPU AI Sovereignty Requires Sovereign Data Infrastructure, Not Just Sovereign Compute

The article argues that controlling GPU clusters alone is insufficient for sovereign AI, since managed preprocessing services, hosted inference APIs, external monitoring, and vendor-controlled orchestration all introduce exposure. It identifies seven AI workload layers requiring sovereignty controls (data ingestion, preprocessing, training, inference, observability, orchestration, distributed training) and recommends keeping all components within the same VPC.