An AI agent creates value when it works with existing business systems. Treat every connection as a governed integration with explicit read, write and approval rights.
Separate reading, recommendation and action
- Define accessible CRM and ERP fields.
- Control document sources and versions.
- Keep secrets server-side and log every action.
- Require approval for sensitive operations.
Test real cases before expanding rights
Measure time saved, answer quality, avoided errors and adoption across common cases and exceptions.
Move from an idea to an operational scope
Document the current process, monthly volume, users, systems, available data, common errors and expected outcome before selecting a model. This baseline makes value measurable and exposes missing data or ownership.
Set autonomy according to risk
Start with read-only access or a draft submitted for human approval. Allow execution only for clearly authorised and reversible actions. Sensitive, uncertain or exceptional cases should be escalated with their context and sources.
Test and measure in production
- Quality on a representative test set.
- Processing time and manual rework.
- Tool errors and human escalation rate.
- Actual adoption by the intended users.
- Cost per completed and accepted operation.
France Num recommends a progressive approach based on concrete business needs, clear objectives and employee involvement. Official guidance: https://www.francenum.gouv.fr/guides-et-conseils/intelligence-artificielle/comprendre-et-adopter-lia/comment-deployer-lia