AI Adoption & Change
AI Champions & Center of Excellence Enablement
Champion networks hold together when mandate, protected capacity, coaching routes, reusable assets, and escalation boundaries belong to named owners and face regular review against the support work teams actually bring.
Champions may already be answering questions between their regular duties. When requests grow, unclear authority and unprotected time become the operating problem. We define the mandate, capacity, coaching rhythm, reusable assets, escalation routes, and contribution review.
At handoff, the program owner has a champion-role charter, coaching cadence, escalation path, reusable templates, and contribution scorecard that managers can operate without private context.


Some of the 500+ brands we've worked with
See all referencesSteps, gates, and who decides
How we work
We design the network around recurring support work, named authority, available capacity, and the point where a champion must hand a case to a specialist or accountable owner.
Mandate comes before activity
We clarify what champions, managers, sponsors, and the Center of Excellence own, where their authority stops, and how much capacity the model needs.
- AI assist
- Automated analysis organizes current champion and manager activity into draft role boundaries for the program owner to review.
- Human gate
- Can every recurring responsibility be assigned without relying on invisible volunteer work? Your program owner decides where champion authority stops.


The rhythm follows support demand
We shape onboarding, office hours, peer exchange, workflow coaching, reusable-asset review, and escalation around the needs of target teams.
- AI assist
- A model can group approved support requests and suggest a cadence for managers and champions to test.
- Human gate
- Which support need does each recurring session or channel address? Managers confirm the cadence solves a genuine support need before it goes live.


The kit works without private context
We prepare role guides, coaching prompts, support routes, templates, and contribution records that the network can maintain.
- AI assist
- A model drafts role guides and templates from approved practice examples for a named champion to review.
- Human gate
- Can a new champion understand the role and start without private knowledge? A named champion reviews the kit before it goes live.


Contribution informs the next review
We define how to review coaching reach, reusable assets, escalations, workflow support, and observed contribution without rewarding activity alone.
- AI assist
- Automated support can compile coaching, reuse, and escalation signals into a draft contribution view.
- Human gate
- Who will use the evidence to adjust the network? Your program owner decides which contribution signal matters most.


Named artifacts you keep
What you get
A new champion can understand the role without private context. Managers and program owners also receive the cadence, escalation record, reusable material, and contribution evidence needed to run it.


Playbook
Champion roles, mandate, and escalation charter
Role definitions, mandate, onboarding, capacity assumptions, manager expectations, and escalation boundaries.


Curriculum
Coaching cadence and specialist-handoff plan
The cadence for onboarding, office hours, peer exchange, workflow coaching, and specialist support.


Workshop record
Escalation-routing and reusable-template log
Templates and records for sharing approved practices, routing difficult cases, and capturing what teams need.


Dashboard
Contribution scorecard and review-rhythm map
Definitions and review points for coaching, reuse, support, escalation, and workflow contribution.
Scope and honest limits
When to bring us in
Questions already reach the helpful people in the organization. Those people may still have no protected time, clear authority, or dependable route for cases that belong with a specialist.
A good fit when
- Different teams expect different things from champions, while managers have not protected time for the role.
- The Center of Excellence publishes guidance, but difficult cases do not move through a dependable coaching and escalation route.
- Community activity and reused assets are counted, yet the review cannot show which workflow received useful support.
- Champion, manager, sponsor, and Center of Excellence roles were never written down, so two people can each assume the other owns an escalated case.
- Onboarding, office hours, peer exchange, and workflow coaching run whenever a champion has spare time, but no cadence says when to expect them.
- Role guides and coaching prompts live in one champion's head, until that person moves on and the network has to relearn what they knew.
- Coaching reach and reuse counts get reported every quarter, yet nobody can say which supported workflow actually improved.
Better handled as other work when
- You want volunteers to carry the adoption work without any manager-protected time. That capacity decision belongs to your leadership, not to this operating design.
- You want the Center of Excellence to decide every local workflow question itself. Local teams keep that authority, and the network only routes the hard cases upward.
- You want contribution targets set before anyone has measured a baseline. A number chosen without that baseline is a guess dressed up as a target.
If one of these is closer to your situation, start here instead: See corporate AI training
Your trainers build AI for a living
The people who run our training build and operate AI systems the rest of the week, so the material comes from work we've shipped. Zeo has been around since 2011 and runs the Digitalzone conference community, which keeps us close to how teams across the industry are picking these tools up.
Tools we use
Tools behind this work
Anthropicone of the model platforms champions field real questions about day to day
Google Geminithe second in-use model platform the champions program has to cover as well
n8nautomates escalation routing so requests past a champion's scope reach the right owner
Datadogtracks support-request volume over time, the evidence cadence gets checked against
Jupyterruns the contribution-review analysis linking champion activity to actual reuse
Next step
Put clear boundaries around champion work


Before you decide




























