Sovereign AI Has Become the Public-Sector CIO's Control Problem
CIO, Thursday, July 23rd, 2026
Public-sector CIOs should prioritize enforceable control across five layers rather than building domestic models.
For most governments, AI sovereignty means enforceable control over data, models, infrastructure, operations and vendor relationships, not necessarily building native models.
Author Collin Hogue-Spears identifies five control layers and advocates a workload-based approach while warning against self-isolation and sovereignty theater.
Success requires classifying AI by risk level, proving data flows, restricting model access, reconstructing decisions, maintaining vendor flexibility and ensuring public accountability. The goal is retaining authority without cutting off access to global innovation.