Governing AI as a System – Part 2 – Special Article

From Policy to Institutional Design.

If Part I established that AI capacity is strategic infrastructure, Part II confronts a more difficult reality: most organizations are not structurally designed to govern AI at scale. In the early phase of adoption, governance largely meant publishing principles.

These were necessary. They signaled intent and established baseline guardrails. But they are insufficient. AI is not a discrete initiative. It is an operating layer. When technology becomes embedded in pricing decisions, credit approvals, hiring pipelines, supply chain optimization, fraud detection, and customer engagement, governance cannot remain peripheral. It must be institutionalized within the enterprise design itself.