The method we apply, for our clients and for ourselves, to turn AI into a lasting capability, in nine chapters: what AI really changes (assistant, enriched automation, agent), the four criteria of a good use case, sizing the return before investing (supervision included), the data rule, the progressive autonomy ladder, shipping without breaking the team's trust, the frame that protects (AI Act, register, charter), visibility in answer engines (AEO) and growing the team. Each chapter ends with an In practice box of three concrete actions and points to the site tool that does the work with you.
What's inside
- Nine chapters, from picking use cases to a lasting capability
- The four criteria of a good first use case and the return-estimation traps
- The autonomy ladder (fully reviewed, spot-checked, autonomous within a scope) and its numeric thresholds
- The AI Act frame in plain words, the data rule, and the AI visibility side (AEO)