In line with this year’s theme, Evaluation, Evidence, and Trust in the Age of AI, this panel brought together members of the EvalforEarth Community of Practice to examine how evaluation could remain credible, inclusive, and context-responsive in an AI-augmented world. Drawing on experiences from Nepal and Georgia, the session offered a cross-contextual reflection on the intersection of policy, practice, and methodology in the use of artificial intelligence for evaluation across food security, agriculture, and rural development.
The panel presented complementary perspectives. Ramesh explored the implications of Nepal’s National AI Policy 2025, the country’s first, for development evaluation systems, governance, and public trust, drawing lessons for countries navigating responsible AI adoption under real infrastructure and data constraints. Dea used Outcome Harvesting as a concrete methodological test case to examine where AI could responsibly support evaluation practice and where human judgement remained non-delegable, bridging field experience across multiple country contexts with reflections on evaluator training at the University of Tbilisi.
These perspectives underscored that maintaining trust in AI-supported evaluation depended not on technological innovation alone, but on human-centred approaches, ethical safeguards, and the capacity of evaluators to critically and deliberately navigate AI’s role in diverse and rapidly evolving contexts.
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