That means defining where AI can assist, where it must be checked, and which outputs require human review. It also means connecting AI to trusted data, adding clear guardrails, and testing results in the same workflows where the work actually happens. When teams treat AI as a tool inside a process, not a shortcut around it, adoption becomes safer and more useful.
