This report investigates whether artificial intelligence can support the harmonisation of impact measurement frameworks in the impact investing ecosystem, drawing on a literature review and 15 semi-structured interviews with investors, founders, researchers, and ecosystem actors. Contrary to the initial assumption that fragmentation is primarily a technical problem, the findings reveal a “credibility-sufficiency equilibrium” where practitioners have adequate measurement tools but lack the incentives to use them rigorously, as impact reporting functions mainly as a trust signal rather than a genuine input into investment decisions. The report concludes that AI cannot resolve this underlying incentive problem, but can meaningfully reduce operational friction by automating reporting, mapping indicators across frameworks, and processing qualitative data. It therefore recommends a two-tier approach: first, convening investors around a shared minimalist reporting standard to raise the credibility floor, and second, developing AI as an operational support layer to help practitioners navigate a still-fragmented landscape more efficiently.