Studio Aletheia Presents · Clarity by Design
An AI Faculty Learning Series
AI Champions Network Sessions
Course 07 of 08 · Coordination, Synergy, and Peer-Led Diffusion
The AI Champions Network is a community of practice for selected representatives across units. Sessions surface real use cases, identify obstacles, coordinate guidance, and keep policy aligned with actual campus work. The goal is sustainable diffusion, not top-down announcements.
Guiding stance: coordination and synergy across units, not top-down announcements.
Core move: turn individual wins into institutional practice through a repeatable session cadence.
Success signal: champions can represent their unit, share what works, flag risk, and carry guidance back in human terms.
Designed for selected faculty and staff representatives building sustainable, peer-led diffusion.
What the network repeatedly works on across meetings.
Sharing Use Cases
Short, repeatable wins. What problem, what workflow, what guardrails, what changed.
Reviewing New Tools
Fast evaluation using shared criteria, not vendor marketing and not social media buzz.
Troubleshooting Challenges
Where implementations break, what misconceptions repeat, and what support fixes it.
Updating Policies and Guidance
Adjust language and examples so it matches real work, while staying safe and consistent.
Avoiding Silos
Cross-unit signals, shared templates, and a consistent message across departments.
Measuring What Matters
Track adoption and clarity, not "AI excitement." Use lightweight indicators that reduce burden.
A repeatable agenda that makes monthly or quarterly meetings productive.
How the network stays coordinated, useful, and sustainable.
- Facilitator: holds the agenda, protects time, maintains the decision log.
- Champions: bring unit signals, share workflows, carry guidance back.
- Policy liaison: ensures updates align with institutional standards and approvals.
- Usefulness, meaning boring, repeatable value.
- Risk, including data sensitivity, compliance, and reputational harm.
- Verification: how outputs are checked, by whom, and for tools that take multi-step or agentic actions, whether those actions are logged and reviewable, not just the final output.
- Equity: who benefits, who gets excluded, who bears the burden.
- Support cost, including training load, documentation load, and maintenance.
- One shared repository for playbooks and templates.
- One decision log, updated every session.
- One "message of the month" delivered across units.
- Rotate spotlight, so innovation is distributed.
Concrete outputs that outlive meetings.
Use Case Cards
One-page workflow snapshots, including constraints, prompts, checks, and safe defaults.
Decision Log
What we tested, what we decided, why, and what conditions must be true for safe use.
Guidance Updates
Short, plain-language policy clarifications with examples, updated as practice evolves.
Troubleshooting Library
Patterns of failure, fixes that worked, and common misconceptions paired with scripts.
Sustainable coordination, built into campus routines.
Shared Language and Faster Support
Units stop reinventing answers, and people know where to go, and what "safe" means.
Consistent Guidance Across Campus
Policies match real practice, and messaging does not fragment into department folklore.
Visible, Repeatable Use Cases
Operational improvements spread via playbooks, not reliance on a few power users.
Governance That Keeps Up
New tools get evaluated with shared criteria, and decisions are documented and revisitable.
Check yourself against the champions model.
A short reflection, plus the self-check this course promised at the start.
One Signal I Would Carry Back
Outcome Guarantee
One agenda item. One artifact.
Name one cadence item you will run at your network's next meeting, and one artifact you will produce from it. Small and specific beats broad and vague.