Impact Engines and the Samoa Bureau of Statistics tested a human-in-the-loop AI workflow to clean a large, complex agricultural survey while preserving statistical oversight and data privacy.
What the case study covers
- How the AI-assisted workflow was structured and reviewed by people.
- Quality-control and privacy safeguards for sensitive survey microdata.
- Time, cost, and reproducibility benefits compared with a fully manual process.
- Practical lessons for national statistics offices and development-data teams.
Read the full case study
The full PDF documents the approach, results, limitations, and recommendations for similar official-statistics workflows.