Manila, Philippines, 1–4 September 2026- The Independent Evaluation Department (IEvD) participated in the eleventh edition of Asian Evaluation Week (AEW) at the Asian Development Bank (ADB) Headquarters in Manila. Held under the theme “Put Your Money Where Your Evidence Is: Institutionalizing Evaluation for Stronger Development Impact.” AEW 2026 brought together evaluation leaders, development practitioners, multilateral development banks, United Nations agencies, governments, and academia to discuss how evidence can better inform policies, investments, and development decisions. The program featured discussions on evidence use, AI, evaluation capacity development, and innovation in evaluation practice.

IEvD was represented at AEW 2026 by Mr. Mirianaud Oswald Agbadome, Senior Evaluation Specialist, and Ms. Dieynaba Niabaly, Evaluation Learning and Outreach Specialist. The Department contributed to two sessions.

Mr. Oswald participated in the panel on embedding evaluation in development decision-making, hosted by the New Development Bank (NDB). The session discussed how development institutions can strengthen the place of evidence in strategic and operational decisions. Drawing on IEvD’s macro evaluation synthesis and its evaluability assessment informing the Bank’s corporate strategy, Mr. Oswald argued that independence of the evaluation function should not amount to isolation. He also called for balancing independence and embeddedness with institutional relevance, strengthening evaluability at design stage, and creating incentives for the systematic uptake of evaluation findings.

On 3 September, Mr. Oswald also moderated the UNFPA and UNDP session “The AI-Augmented Evaluator: Redefining the Evaluation Cycle”. The panel, which featured the Director of the UNFPA Independent Evaluation Office, the UNDP Regional Evaluation Advisor for Asia and the Pacific, and a representative of the ADB Independent Evaluation Department, examined how AI is transforming evaluation practice across the evaluation cycle, including evidence synthesis, data analysis, reporting, and knowledge management. Participants noted that while AI can significantly improve the quality and timeliness of evaluation products, evaluators must stay in the driver’s seat on what counts as credible evidence.

The discussions across all sessions reflected one key message: strong evidence does not appear on demand; it must be generated with rigor and then used effectively. This is where artificial intelligence carries its clearest promise: improving the quality of evidence generation and shortening the time it takes, which in turn expands the opportunity for evidence to influence policy and investment decisions. For an institution like IsDB, putting the money where the evidence is, means investing in the data and systems that produce evidence, a governance framework that sets the terms for using new tools, and staff capacity to interrogate what those tools produce and to act on the findings.