How to ensure network success: Only by having direct access to the core AI program team will your AI champions be able to escalate blockers, share wins, or ask questions. What they surface will include everything from permissions problems to policy gray zones to unplanned usage patterns that could be scaled into formal solutions. That signal is valuable, but it only flows if the loop is tight.Visibility is also critical to success. Recognize champions publicly. Feature their contributions in newsletters, all-hands meetings, or town halls. Encourage business unit leaders to nominate future champions and to celebrate those already active. Reinforce the importance of the role by showing how it connects to larger goals such as productivity, efficiency, or time-to-decision. When possible, collect and publish short “reinvestment reports”, real stories showing how time saved through gen AI was redirected to higher-value work. This gives executives context and creates institutional memory.To track performance, look beyond usage dashboards. Metrics like “weekly active users” miss nuance. Monitor champion activity by measuring how many teams are activated, how many use cases are surfaced and adopted, and what level of usage teams are reporting. If you’re supporting custom GPTs or internal agents, track how many are being built, shared, or certified. If you’re running learning paths, measure participation and progression. And wherever possible, track how saved time was reinvested. Leaders don’t just want to know that people saved 30 minutes per week. They want to know where that time went and who benefited from it.
Champion network challenges: You will encounter challenges establishing and building out your AI champions network. Some AI champions will go quiet. Some business units will opt out entirely. Others will over-index on experimentation without tying anything back to work. That’s normal, and why you should revisit your champion mix every quarter to rotate people in and out. Recruit fresh voices. Don’t let the network ossify, and don’t let the rhythm break. A champion program without regular connection points, real work, and shared recognition will decay into a title with no impact.What makes this network work is credibility. Champions should be embedded in the business, not watching from the sidelines. They need to be close enough to the work to answer questions, run small experiments, and identify what matters. The program should be lightweight but supported. Enable them with tools, training, and access. Give them structured but flexible ways to engage. Show their impact and grow the program based on what’s working. When that foundation is in place, the network becomes self-sustaining.Done right, an AI champions network is how a generative AI capability moves from the center of the org chart to the edges. It’s how you transition from early adoption to distributed enablement. It is the mechanism that turns individual exploration into team-level practice and sets the stage for scaled workflows, role-based orchestration, and deeper business alignment.That next stage is coming quickly. As core usage stabilizes, your most engaged users will begin building on top of the assistant. They will want to customize its behavior, tailor it to specific tasks, and create lightweight agents that complete work on their behalf. The groundwork for that evolution is cultural and architectural. But the signal that you are ready will come from one place: your champions.See also:
The CISO’s guide to rolling out generative AI at scaleShadow AI is surging, getting AI adoption right is your best defense
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