Agentic CI : from digital continuous improvement to agentic continuous improvement
How AI, embedded in the rituals your teams already run, learns from the shop floor and spreads knowledge across all your sites.
Digitalization has solved many of the frictions in continuous improvement, but not all of them: knowledge stays local, know-how evaporates, recurring patterns stay invisible. And while nearly 90% of organizations are already experimenting with AI, only 7% manage to deploy it across the whole company.
Download our guide to discover how to bring continuous improvement into the agentic era: by building on your daily management rituals, on a business ontology designed for agents, and on the trust of your shop-floor teams.
15 October 2026
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Guide
What you’ll learn in this guide
Agentic CI : from digital continuous improvement to agentic continuous improvement
The 4 problems that digitalization has not solved, and what agentic CI changes
Why an AI agent does not learn in a vacuum: the role of the business ontology and of Essential Domain Intelligence
A 4-step roadmap and prerequisites to success
Sommaire
1. Executive summary
A new era for continuous improvement.
2. After digitalization: what remains to be solved
Local knowledge, evaporating know-how, invisible recurring patterns, maturity that is hard to assess: four problems and how Agentic CI answers them.
3. What AI needs to learn: the foundation that makes an agent useful
Why an agent does not reason from scratch: business ontology and Essential Domain Intelligence.
4. AI multiplies shop-floor expertise, but nothing works without team trust
Perceived surveillance, devaluation of skills: how to anticipate both legitimate fears.
5. The roadmap to agentic continuous improvement
The 4 steps to Agentic CI and the and the crucial role of data governance across sites
6. Choosing the right tool: the real issue is not the software, it is its foundation
Why choosing a daily management solution means choosing a foundation for ten years.
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