Collective Learning in Philanthropy: AI, Trust, and the Future of Grant Reporting
Year: 2025
Type: article
Abstract: Grant reporting has largely devolved from a learning tool to a bureaucratic exercise that reinforces power asymmetries and burdens nonprofits. As philanthropy confronts mounting crises demanding equity and transparency, reporting must transform into a space for collective sensemaking. This paper explores how Artificial Intelligence (AI), paired with Oral and Alternate Reporting (OAR) methods, can build equitable, human-centered reporting systems. We propose the E4 framework — Efficiency, Effectiveness, Expansiveness, and Equity — for intentionally leveraging AI in service of more equitable reporting practices. Traditional reporting often sidelines the expertise of nonprofit staff and communities most affected by funded programs. Drawing on our own AI experimentation and grantee partnerships, we offer design principles and micro-moves for immediate implementation. We call on philanthropic leaders to both reposition reporting as a strategic site for trust-building and to intentionally leverage AI to support innovation and transformation in grant reporting that centers community voice, advances equity, and enables the collective learning essential for addressing complex social challenges.
Source: The Foundation Review
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7127038266
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