Scoping Study on the Use of Artificial Intelligence in Climate Change Evaluations
Technical Evaluation Reference Group of the Adaptation Fund (AF-TERG), Climate Investment Funds (CIF)
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Abstract: This scoping study?jointly commissioned by the AF, CIF, GEF, and GCF?explores how artificial intelligence (AI), especially generative models, can be applied in climate change program evaluations. Through a literature review, 19 stakeholder interviews, and a global evaluator survey, the study maps AI applications across evaluation phases, including data analysis, qualitative coding, and summary generation. It discusses real-world use cases from international organizations, identifies promising tools (e.g., LLMs, NLP, satellite-imaging models), and outlines benefits like cost efficiency, analytical speed, and expanded data reach. Equally, it emphasizes risks?hallucinations, bias, overautomation?and calls for cautious, supervised use. The study delivers strategic recommendations for climate funders on AI integration, workforce capacity, and ethical oversight.