This session introduced an AI-driven approach to uncovering drivers of effective policy coherence in climate and sustainable development policy implementation across diverse governance contexts. By integrating established policy evaluation frameworks with Natural Language Processing, the session presented a method for systematic analysis of large volumes of policy evaluations, audits, and grey literature.
The methodology focuses on i) the policy implementation processes and their role in delivering successful policy outcomes; and ii) mapping of recurring success patterns across countries, sectors, and policy domains, highlighting both common drivers and context-specific variations. This approach enables comparative analysis that reveals ‘hidden’ insights that could support more targeted and effective policy interventions and financing strategies that are adapted to domestic social, political, and economic contexts.
The session also outlines how this work can form the foundation of a broader platform for knowledge and data sharing on climate policy implementation that offers actionable, evidence-informed insights that can accelerate progress on climate action and sustainable development by integrating countries’ global commitments and domestic priorities.
Opening Remarks
- Carlos Manuel Rodríguez, CEO and Chairperson, GEF Secretariat
Moderator
- Sonja Sabita Teelucksingh, Adviser, GEF Secretariat
Speakers
- Adis Dzebo, Senior Research Fellow, SEI Headquarters
Documents