Supervised AI trial for ENAC technical documentation
Controlled use of AI-assisted drafts, LaTeX structure, and human review to evaluate speed and quality in technical syllabus documents.
Step 01
Problem
An ENAC regulatory change plus several nonconformities required a high volume of technical syllabus review under time pressure.
Step 02
Context and constraints
The team needed to move quickly without losing technical judgment, and the process was used to test how far AI could help in a draft-only phase.
Role: Contributed to the documentation strategy: AI-assisted drafts, LaTeX structure, and human review while keeping the documents as supervised material.
Step 03
Key decisions
- Use AI as first-draft support, not as a replacement for expert judgment or final review.
- Standardize output in LaTeX to preserve consistency and reduce editing friction.
- Intervene only as much as needed to evaluate the real quality of supervised AI-assisted output.
Step 04
Outcomes
- The process worked as an internal capability test for producing reviewable technical drafts faster.
- Human review separated useful AI output from points that required technical judgment.
- The team gained a reusable learning base without presenting AI as an automatic quality guarantee.
Metrics
- Approximate batch of 40 technical syllabus documents used as the supervised test scenario.
- Hybrid workflow: assisted draft, LaTeX structure, and human review.
- Learning applied to technical documentation sensitive to regulatory criteria.
Step 05
Learnings and next improvement
Learnings
- In regulated documentation, AI can accelerate a draft, but the real value depends on human review and knowing where not to delegate.
- Testing a tool’s limits in a controlled setting helps decide whether it deserves to become a stable workflow.
Next improvement
- Define internal criteria for documentation AI: when to use it, when to reject it, and how to record the review performed.
Link
Step 06
Visual resources
