Report produced by Becca Portman, Community Success Lead at The Patrick J. McGovern Foundation
Across the country, communities are making decisions today that will shape their energy future for decades. Yet the information that could guide those choices is often hard to find, hard to understand, or arrives too late to act on.
At PJMF, we work with partners to close gaps like these by identifying unmet needs, prototyping tools, and sharing learnings that others can build on. Earlier this year, we explored how AI could help local green space advocates and planners work more effectively, publishing a report on our findings. Building on that foundation, we turned our attention to a related challenge: how AI and data could support communities in advancing local renewable energy projects. When many communities are equipped to act, their collective efforts can add up to a meaningful shift in the pace and scale of the clean energy transition.
We began this exploration with a simple idea: AI might help make project information clearer and more actionable for local advocates. As we mapped the renewable energy data landscape, however, we also saw another need: using AI to make the data itself more accessible for researchers and nonprofits, so they could generate the reliable, structured insights that advocacy depends on. This report traces both of those threads: the potential for AI to help communities act with confidence, and the potential for AI to help researchers provide better inputs into that process.
🗺️ How to navigate this report: Click on the arrow to expand each segment of the report below.
💬 Questions, comments or ideas for collaboration? We’d love to hear from you. Reach us at [email protected].