AI Adoption Readiness Sprint
A short, focused engagement to turn uneven adoption into operating rules and a rollout plan.
Best for
- AI pilots exist, but usage is inconsistent
- Quality debates / rework loops are rising
- Policy, risk, and “what’s allowed” is unclear
- Leaders want progress without forcing “training theater”
What you get
- Clear adoption diagnosis
- Operating rules + decision rights
- A 30/60/90 rollout plan with measurable moves
3 Phased Approach
Reality Check (Discovery)
Goal: Turn interview noise into a clear typology and friction map.
Includes
- 20+ interviews across leaders / managers / ICs
- Adoption Typology Matrix + key profiles
- Friction Map (where adoption stalls and why)
Output: what’s blocking adoption + what needs to change first
Operating Model (Design)
Goal: Define the rules of the road.
Includes
- Usage standards (assist vs decide, verification norms)
- Guardrails (safe use guidance + escalation path)
- Decision rights + ownership (who approves what; what “good” looks like)
Output: operating rules leadership can stand behind
Rollout (Delivery)
Goal: Move from “testing” to “scaling.”
Includes
- 30/60/90 plan: sequencing, comms, enablement moves
- Segment-specific interventions (fear vs skepticism, internal vs external)
- Simple measurement plan (usage consistency, cycle time, rework)
Output: what’s blocking adoption + what needs to change first
Deliverables, timeline, and what happens next
Typical deliverables
- Adoption Typology + Friction Map
- Operating rules + guardrails (plain English)
- Decision rights + accountability map
- 30/60/90 rollout plan + leadership messaging pack
- Measurement checklist
Timeline
- Usually 2–4 weeks (depends on interview scheduling)
After the sprint
- Option A: You run it internally using the plan
- Option B: We stay on as a light retainer to support rollout + iteration
FROM SHELFWARE TO TAKEOFF