Observation
AI governance is often associated with approvals, compliance and controls at the end of a project. In reality, many of the decisions that determine risk happen much earlier.
From the Field
Even at the point of defining an AI use case, you're already making governance decisions: what data it can access, what it is allowed to do, who sees the output, where human review sits and who owns the result. Waiting until go-live to ask those questions means some of the most important decisions have already been made.
Why This Matters
Good governance doesn't have to mean slowing everything down. Building the right questions into design from the beginning is usually easier than trying to retrofit controls later.
Field Takeaway
AI governance starts with design, not go-live.
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