The annual SDG financing gap stands at roughly $4 trillion, yet the constraint is increasingly the coordination cost of deploying capital. Across governments, DFIs, MDBs, foundations, UN agencies, NGOs, and investors, three failures limit effective matching: incompatible institutional vocabularies, complex mandates and eligibility requirements, and differing evidentiary standards for development and commercial capital. The result is a costly mismatch in which strong programs remain unfunded while earmarked capital goes undeployed.
This private roundtable will explore whether agentic AI can provide evidentiary translation infrastructure between funders and implementers. Combined with open standards such as the Model Context Protocol (MCP), agents could interpret mandates, reconcile constraints, assemble evidence, and match funding to programs while preserving institutional data sovereignty. The discussion will focus on where coordination costs are greatest, what governance and auditability are needed for trust, whether open protocols can become shared impact infrastructure, and which pilot could demonstrate the model most credibly.
Energy, Environment, & Transition
Studio Stage: A Pro-Market Path to Decarbonization
Efforts to decarbonize the global economy have increasingly run into political and practical challenges, with top-down approaches often proving fragmented, slow, or contested. In this Studio Stage talk, Professor Karthik Ramanna explores a pro-market approach to decarbonization, highlighting how rigorous…
