AI governance often looks complete on paper while remaining weak in daily operations. This episode examines why policies, committees, and principles only become effective when they are connected to live management routines.

It explores governance as an operating rhythm for scaling AI with control and confidence.

TLDR / At a Glance

• Policy-to-practice governance gaps
 • Cadence, monitoring, and escalation
 • Ownership across workflows and vendors
 • Dashboards linking risk and value
 • Proportional controls by risk level
 • Governance as performance infrastructure

The central takeaway is that AI governance works when leaders run it continuously through the same systems that manage the business.

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