How to Build M&E Workflows with Quality Controls

Participants will leave this session able to build a structured, quality-controlled M&E workflow using AI tools, one they can adapt immediately for their own tasks. They will understand why single-prompt AI use fails for complex M&E work, how to decompose a task into stages that produce consistent output, how to ground AI in domain-specific M&E criteria rather than its own general judgment, and how to install quality checks that catch problems before output is accepted.

The session uses survey design as a worked example throughout. Each component is demonstrated live and explained in terms of what it does and why it matters, so participants leave with a mental model they can apply across different M&E tasks, not just the one covered in the session. A completed reference workflow is shared for participants to take and adapt.