The risk profile changes when AI becomes infrastructure
An employee using AI to draft a note creates a different risk than a company routing customer data, campaign decisions or production workflows through automated systems. The more central AI becomes to operations, the more deliberately organizations need to define controls.
Quality risk is often hidden by speed
AI can produce plausible output quickly. That makes review discipline important, particularly for factual claims, regulated content, brand-sensitive communications and decisions that affect customers or budgets.
Governance should follow workflow importance
Organizations do not need the same controls for every use case. A useful model is to classify workflows by data sensitivity, external impact, reversibility and the level of human judgment required, then set review gates accordingly.
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