AI for M&E: A Practitioner's Resource

Guides for M&E teams using AI, from writing better prompts to governing AI use across your organization. Everything here is free.

Playbooks

Step-by-step playbooks for the M&E tasks every team runs from scratch every cycle. Each one runs in a single AI conversation and produces a complete output.

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Build a MEL Plan with AI

A 5-step prompt workflow that produces a complete Monitoring, Evaluation, and Learning plan with results framework, indicator matrix, data collection plan, reporting schedule, and learning agenda.

You end up with: A complete MEL plan with results framework, indicator reference sheet, data collection plan, reporting schedule, and learning agenda.

Code Qualitative Data with AI

A 5-step prompt workflow that takes raw interview or focus group transcripts through to a coded dataset with thematic analysis. Run all prompts in a single AI conversation.

You end up with: A codebook, coded dataset organized by theme, and a thematic analysis summary with illustrative quotes.

Create a Donor Report with AI

A 5-step prompt workflow that produces a donor-ready progress report with data summaries, narrative, evidence integration, lessons, and recommendations.

You end up with: A donor-ready progress report with executive summary, indicator data table, narrative sections, lessons learned, and prioritized recommendations.

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AI for M&E Guides

Walk-through guides for every major M&E task. Each one has a step-by-step workflow, copy-paste prompt templates, and an approach grounded in M&E practice.

All 13 guides

How to Clean Messy M&E Data with AI

Turn 15 hours of manual cleaning into 2 with a 4-step workflow that combines free tools and AI validation to catch errors human review misses.

Analysis

How to Build Better Surveys with AI

Most AI survey tools stop at generating questions. This guide covers the full lifecycle: choosing question types, catching bias, adding skip logic, and piloting before you deploy.

Data Collection

How to Draft Evaluation Reports with AI

Stop staring at a blank page. A 4-phase workflow turns your completed analysis into donor-ready evaluation narrative in hours, not days.

Reporting

How to Code Qualitative Interview Data with ChatGPT

Turn 30 pages of evaluation interview transcripts into validated themes in 2 hours instead of 3 weeks. A 4-step workflow that pairs AI pattern recognition with the human analytical judgment that makes the findings defensible.

Analysis

How to Build a Theory of Change with AI

Stop drawing boxes and arrows that nobody believes. A 4-step workflow that uses AI to surface hidden assumptions, stress-test causal logic, and produce a ToC your donors trust.

Planning

How to Quality-Assure AI-Assisted M&E Work

AI produces confident-looking wrong answers. Without a validation stack, you publish them. This 6-layer framework gives your M&E team the discipline to catch errors before they reach donors, boards, or communities.

Governance

How to Get Reliable AI Outputs in M&E Work

Cloud AI is confident and fluent and sometimes just wrong. For M&E work that feeds into evaluations, donor reports, and funding decisions, fluent-sounding errors are the enemy. This page covers the practical moves that reduce AI failure rates: hallucination prevention, local model use, quality control patterns, and pipelined AI.

Governance

How to Use AI to Write a MEL Plan

A MEL plan is the most requested M&E deliverable, and the most time-consuming to write from scratch. AI can draft the structure, populate indicator tables, and flag gaps, but only if you guide it section by section.

Planning

Foundations

The skills and safeguards that apply to every AI-for-M&E task.

Get started with AI

Use AI responsibly

More in the toolkit

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Free M&E Tools Prompt Library