Rotating membership keeps the energy fresh and prevents ownership from consolidating in a small group. Participation should be visible but low-friction. Let employees opt in, participate in one quarter, rotate out, and rejoin later. Encourage teams to nominate new participants as adoption expands. Think of the network as an active community of practice, not a fixed committee.
Once participants are identified, onboard them with precision. The kickoff session should establish scope, expectations, and structure. Champions are not AI policy enforcers. Their role is to guide their teams, connect AI to the real work happening in their area, and provide early feedback on adoption blockers and emerging use cases. The session should include persona-based workflows, not just general use cases. Walk through how AI helps a project manager, an HR business partner, or a supply chain analyst. Equip champions with internal prompt libraries, GPT catalogs, and use case collections. Give them language they can use to onboard peers without having to create materials themselves. Run live learning sessions or internal hackathons to solidify understanding and build momentum.
Operational cadence also matters. Without rhythm, the network will stall in 60 to 90 days. Establish a monthly sync; not as a status update, but as a working session to share what’s working, swap ideas, and discuss problems. Give the network a persistent digital space in Slack or Teams to post prompts, updates, and experiments. Reinforce a “yes, and…” mindset in those spaces. That tone keeps the threshold for sharing low, which matters if you want early-stage usage to grow into repeatable patterns.
