• AI policies aren’t enough; without clear ownership and decision rights, governance falls apart the moment something goes wrong. • Credit: Hassan Pasha Most enterprises are writing AI policies right now. • They are also standing up review boards, model inventories, and risk registers. • Then the first real incident happens: An agent changes a configuration. • A staff member pastes sensitive data into a tool they were not approved to use. • A model output drives a decision nobody can fully explain.

Article Summaries:

  • AI experts argue that current corporate AI policies fall short because they lack clear ownership and decision‑making authority, leading to governance failures when incidents occur. The article introduces “institutional sovereignty” as a missing governance layer that emphasizes authorship, accountability, and continuity, enabling leaders to trace who authorized actions and who is responsible for outcomes. It explains why AI adoption stalls-contractual ambiguity and liability uncertainty create a “wild west” environment, especially in healthcare, where policy describes intent but offers no proof of who acted. The piece cites NIST’s AI Risk Management Framework and ISO/IEC 42001, both framing AI governance as an organizational system rather than a technical checklist.

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