Treating AI compliance as a final review step is fundamentally broken because AI systems change continuously between audit cycles. Drawing on research into China's generative AI regulatory filing process and the EU AI Act, the author argues governance must be embedded directly into the CI/CD release pipeline rather than bolted on afterward. Three concrete shifts are recommended: auto-generating model documentation (model cards, data provenance) as pipeline artifacts, making compliance evidence a hard deployment gate alongside existing security checks, and treating AI agent identities as first-class IAM controls with scoped permissions and audit trails. Organizations that build governance into release infrastructure now will be better positioned when AI-specific mandates from the EU AI Act, US state laws, or sector regulators arrive.
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