06 / ADOPTION
AI Adoption and Operating Capability
We run role-based use, leadership ownership, measurement, and product improvement as one operating model.
Adoption is not training alone. Role-based workflows, leadership ownership, an AI-pioneer network, and safe-use materials build new working behavior; usage and outcome signals show where the product needs to change.
Go-live is not the final step. Product feedback, improvement, and managed AI operations keep the system useful in daily work. This is not a generic corporate AI training service.
Place in the method
- 01Map
- 02Prioritize
- 03Prove
- 04Build
- 05Embed
- 06Compound
FLOW
How it runs
Each stage leaves an artefact behind; the next one builds on it.
- 01
The usage line
Who, in which flow, with which tool: the target behavior is written role by role and compared with today's reality. Criteria are in the language of behavior, not of tools.
ARTEFACTAdoption plan
- 02
Role-based program
Training is not generic; each role learns on real examples of its own work. Leadership activation is part of the program, not its decoration.
ARTEFACTRole programs
- 03
The champion network
Ownership is not imported; it is built from inside: champions carry the rhythm, and feedback lands on the product's improvement line.
ARTEFACTChampion network
- 04
Measurement and operations
Usage and outcome signals are reviewed on a steady rhythm; product optimization and managed AI operations attach to that rhythm.
ARTEFACTUsage board
What we produce
- Organization-wide AI operating model
- Role-based use design
- Leadership ownership and champion networks
- Usage and business-outcome measurement
- Continuous product improvement
- Managed AI operations
When it is the right step
- The tool was bought, usage stayed low
- There is no scale-up plan after the pilot
- Continuous operations lack an owner
When it is not
If there is no product to use yet, there is nothing to adopt; the problem and its order come first.
AI Opportunity Discovery & StrategyIf usage is low because the product does not fit the flow, training will not cover for it; fix the product first.
Custom AI Products
Outside the scope
- Training does not rescue a product that does not fit the flow; if the problem is the product, the adoption program says so instead of hiding it.
- The lasting owner of adoption is the organization itself; we build the rhythm, measure it, and hand it over — we do not sell a permanent dependency.