AGENTIC AI AND IMPACT FUTURES MARKETS: ALIGNING INCENTIVES FOR ADAPTIVE, OUTCOMEORIENTED PROJECT MANAGEMENT

Traditional Results-Based Management (RBM) frameworks in international development remain constrained by linear control cycles and retrospective evaluation, creating a persistent misalignment between short-term delivery incentives and long-term development outcomes. This paper reconceptualizes project management as a problem of dynamic incentive alignment under uncertainty, enabled by Agentic AI with a human-in-the-loop. It develops an integrated framework in which continuous algorithmic triangulation aligns delivery performance, risks, and underlying assumptions with intended outcomes, generating forward-looking probabilities that guide real-time decision-making. These probabilities are capitalized through Tradable Impact Assets (TIAs), linking expected future impact to present incentives and enabling continuous incentive alignment, and enabling endogenous pricing of project quality. A Complementary impact-market architecture supports prospective valuation and ex post outcome verification, extending incentive structures beyond project completion. By embedding learning, valuation, and financing within project execution, the framework shifts project management from static delivery toward adaptive, incentive-aligned outcome stewardship.