
AI Governance
Before Scaling AI, Build the Operating Model
A short institutional checklist before widening deployment beyond early adopters.
If you scale before you know how decisions are made, who is accountable, and how quality is measured, you do not get speed. You get drift.
Three design questions
Who can stop a deployment? How is human judgement preserved where it matters? What evidence would change your mind?
A practical sequence
Stabilise workflows, clarify ownership, then widen access — not the reverse.
About the author
Qiqing He works at the intersection of artificial intelligence, workforce transformation, education, and public-interest institutions, translating technical change into institutional readiness.
