How AI is changing monitoring and evaluation

Monitoring, evaluation and learning teams spend much of their time on tasks AI does well: cleaning data, coding qualitative responses, summarising reports and producing the same charts every quarter.

Qualitative data at scale

Community feedback, focus group transcripts and open-ended survey answers often go under-analysed because coding them by hand takes weeks. AI can propose themes in minutes, which analysts then review, refine and validate.

Faster, better reporting

AI can draft narrative sections of donor reports from your indicator data, leaving staff to check accuracy, add context and focus on what the findings mean.

Keep humans in the loop

AI makes mistakes and can reflect bias. Good practice is to validate a sample of AI-coded data, document how AI was used, and protect beneficiaries' personal data at every step.