The difference between AI tooling and AI governance
AI tooling is about productivity. AI governance is about control, review, and evidence. You can have both, but they solve different problems and should not be confused.
AI tooling: speed and adoption
Tooling focuses on helping teams work faster: drafting responses, summarizing documents, assisting with code review, and automating routine tasks. It is about outcomes and convenience.
AI governance: policy and accountability
Governance focuses on what is allowed, what requires approval, and what must be blocked. It provides evidence of decisions and defines what should be logged. This is the layer that makes AI defensible in real operations.
The bridge: a gateway
An AI gateway connects the two. It lets teams keep the speed of AI tooling while enforcing policies, routing high-risk actions to approval, and recording decision metadata. That makes adoption safe and review-ready without overpromising compliance.
Next step
If your tooling is moving faster than governance, a short pilot can restore control. Start with a single workflow and define approval boundaries before expanding scope.