Remove unnecessary risk
Most organizations cannot support every public AI device, and they should not try. Once an enterprise platform goes live, decide whether access to public tools such as chat, Gemini, or Cloud will be restricted. It is not about fear or boundary. It is about stability and visibility. If users can find high-quality output inside a safe, ruled environment, then unmonitured is less justified to use public tools. Removing unnecessary risk is part of responsible competence. It also confirms that the enterprise is not only a set of rules, but is investing in a real solution.
Strengthen learning and safe use principles
Once the foundation is in place, the AI champion should be closed. The growth should go through the network. Competent questions should be answered locally. Keep flowing on communication. Keep publishing examples. Make it easier to learn from others. Create internal channels where users can share signals, victory, learned lessons and reactions. Regarding regular safe use principles, not reactively. Governance should be active, visible and helpful; Not reactive, invisible or punitive.
Level to your AI Foundation
At this stage, your AI deployment has gone into production from the pilot. You have a safe, accessible tool. You have clear policies and training. You have a distributed network of AI Champion, live use cases and active response loops. You are not just rolling out a technique: you are enabled a capacity. The stage is no longer a point. The value is how people use it.
