AI transformation12/12/2025 • 8 min read
ACTIVE → ITERATION → ADOPTION: a simple method to industrialize AI
How to move from experimentation to production: framing, fast iterations, and adoption measured with usage KPIs.
ACTIVE → ITERATION → ADOPTION
1) ACTIVE: align key stakeholders
Goal: align leadership, business teams and IT around concrete use cases.
2) ITERATION: prototype fast, learn fast
We favor short loops, user feedback, and guardrails.
3) ADOPTION: measure, improve, roll out
Adoption must be managed: usage KPIs, satisfaction, quality, ROI.
Example checklist
- prioritized use case
- accessible data
- risk / compliance framed
- deployment + monitoring
type Kpi = { name: string; target: number } const kpis: Kpi[] = [ { name: "Active users", target: 200 }, { name: "Tasks automated / week", target: 1200 }, ]
Related articles
Practical guides
AI agents: conversational, scheduled, event-driven — how to choose?
A quick guide to choose the right AI agent type based on your workflows, data, and stack constraints.
Customer stories
Field feedback: an AI hackathon as an adoption catalyst
Why the hackathon format creates fast, visible outcomes and gets teams on board.
If you’re at this stage…
We can turn these ideas into concrete outcomes: start with a diagnostic (prioritize) or a first agent (ship).