"AI is racing ahead in philanthropy and nonprofits.
But the people closest to communities aren’t writing the rules. We kept hearing fear, hope, and confusion in the same breath.
So we built a project that listens at scale—data, stories, disaggregated truths.
To make sure AI in our sector is shaped with nonprofits, not done to them."
-Meena Das, Founder of the AI Equity Project on why this project exists
2024-2026
3 years of nonprofit AI Equity research
2400+
nonprofit staff and leaders surveyed across the U.S. and Canada
3000+
report downloads and readers across the sector
30+
keynotes, webinars, and workshops shaped by insights from the AI Equity Project
Mark Your Calendars:
AI Equity Project Report 2026 RELEASING ON SEPTEMBER 29th, 2026!
Our Project Sponsors
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THE SHORT VERSION
Our Project Sponsors
The AI Equity Project is a multi-year research and listening initiative examining how nonprofits in the U.S. and Canada are using, experiencing, governing, and resourcing AI.
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Across 2024–2026, more than 2,400 nonprofit staff and leaders shared data and stories about AI use, readiness, bias, data equity, governance, funding, power, and accountability.
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We disaggregate findings by factors such as organization size, geography, role, and identity to surface where the benefits, risks, and resources around AI are uneven.
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The purpose is simple: give nonprofits, funders, technology partners, and sector infrastructure organizations evidence they can use to make AI decisions that center equity—not just efficiency.
The research now also informs the AI Equity Framework, practical workbooks, checklists, and sector conversations designed to help organizations move from awareness to more accountable practice.
THREE YEARS, ONE EVOLVING STORY
How the AI Equity Project evolved
2023
THE QUESTION
As generative AI accelerated across philanthropy and nonprofit work, we saw a critical gap: the people closest to communities were rarely the people shaping the rules, tools, or funding decisions around AI. We began with a question: if our sector does not actively shape how AI enters our work, who will?
2024 - the Launch Year
ESTABLISHING THE BASELINE
We asked more than 700 nonprofits how they were experiencing AI, data equity, readiness, and risk. The picture was one of cautious curiosity. AI was already appearing in day-to-day work, but readiness, governance, and clarity were low. Many organizations were still asking foundational questions: What is this? What could it do? What should we be worried about?
2025
MOVING FROM AWARENESS TO DESIGN
By year two, experimentation and familiarity had accelerated. Nonprofits were no longer only asking whether AI mattered; they were asking what training, leadership, funding, data practices, and governance they needed to engage with it responsibly. Use was growing faster than the infrastructure around it.
2026
ADOPTION BRINGS HARDER QUESTIONS
By year three, AI had become widespread—formally and informally. The harder questions became: Who decides which tools are used? Who is accountable when something goes wrong? Who pays for responsible adoption? Whose voices shape these decisions? And how do we know whether AI is actually improving mission outcomes?
Across three years, the story moved from fog → naming → adoption.
The next phase is not simply about using more AI. It is about deciding when to use it, who should shape those decisions, and what accountability should look like when the consequences become real.
FINDING
What three years are telling us
01
AI adoption is moving faster than governance
AI is no longer hypothetical. In 2026, nearly 70% of respondents reported some organizational AI use, while only 12% said that use was guided by organization-wide practices or expectations. AI often becomes organizational practice before organizations have decided what responsible practice requires.
02
Readiness is growing—but shared alignment is not guaranteed
Organizations increasingly describe themselves as ready to integrate AI, but readiness does not mean everyone is moving together. Leadership silence, staff experimentation, approved tools, resistance, and uncertainty can all exist inside the same organization. Responsible adoption is a culture and governance challenge, not only a technology challenge.
03
AI can be inexpensive to start—and expensive to understand
Nonprofits are often absorbing AI through free tools, existing software, internal budgets, and even staff members paying personally. The cost of beginning may be low; the cost of understanding impact, risk, evaluation, data practices, and accountability is not. In 2026, difficulty measuring AI impact became the most commonly selected challenge to securing AI-related funding.
04
Philanthropy is shaping AI even when it is not consistently funding readiness
Funders influence AI through expectations, application processes, learning opportunities, and signals about what organizations should adopt. But encouragement to use AI is not the same as funding staff time, governance, evaluation, community participation, or response when harm occurs.
05
Equity requires attention to power—not just better tools
Across the project, the recurring questions are not simply whether AI works. They are who has a voice, who has resources, who carries risk, who can refuse, who is accountable, and whose definition of success shapes the system. That is why the project continues to treat AI equity as an evolving practice rather than a score.
EXPLORE THE RESEARCH
Three years, three annual studies
FROM RESEARCH TO PRACTICE
Evidence, then a way to act on it
The AI Equity Project began as a research and listening initiative. Three years of findings made one thing increasingly clear: the sector does not only need more evidence about AI. It needs practical ways to make decisions about AI with greater care, transparency, accountability, and community voice.
AI Equity Framework
In 2026, the research took shape as a six-layer framework connecting Data Equity, Transparency, Accountability, Resource Equity, Co-Design and Participation, and Power and Self-Determination. The framework gives nonprofits, funders, and technology partners a shared structure for examining whether AI decisions distribute benefits, risks, voice, and responsibility fairly.
AI Equity Toolkit
The project also turns research into practical resources teams can use in real time. The toolkit includes the AI Equity Checklist for Fundraisers and AI Equity Workbooks for nonprofits, foundations, and technology companies—designed to help teams ask better questions about risk, power, governance, participation, and accountability before scaling AI.
Research tells us what is happening. The framework and toolkit help us decide what to do about it.
RESEARCH IN THE FIELD
Our Media Partners
The AI Equity Project has informed critical analysis, sector conversations, keynotes, webinars, and practical guidance across nonprofit and philanthropic spaces.
WHAT'S NEXT
The research is three years old. The questions are not finished.
The AI Equity Project has now created three years of sector learning. The next chapter may include deeper qualitative research, practical tools, community-led learning, new partnerships, or another survey cycle—but the purpose remains the same: make sure the people and organizations closest to communities have a meaningful voice in shaping what happens with AI in our sector.
WE ARE ESPECIALLY INTERESTED IN
expanding participation beyond the U.S. and Canada;
deepening analysis of identity, organizational power, leadership, and AI decision-making;
creating more space for nonprofit practitioners to share stories of experimentation, refusal, harm, learning, and adaptation;
strengthening partnerships with nonprofit networks and communities underrepresented in AI conversations; and
bringing funders, nonprofits, technology partners, and communities into dialogue so findings influence practice—not simply document it.
ABOUT
AI EQUITY FRAMEWORK
Over the past three years, the AI Equity Project has evolved from a research initiative into a practical body of work designed to help the nonprofit sector navigate AI adoption with greater care, accountability, and equity. Through surveys, sector listening, and ongoing conversations with nonprofit practitioners, the project has tracked a growing gap between rising familiarity with AI and the systems needed to govern it responsibly. That pattern revealed a clear need: nonprofits did not just need more tools or more excitement about AI — they needed a stronger way to think about power, accountability, transparency, and community impact in AI use.
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In 2026, that learning has taken shape as the formal AI Equity Framework — a six-layer framework built from real sector tensions, not abstract theory. Grounded in themes such as data equity, transparency, accountability, resource equity, co-design, and power, the framework helps nonprofits, funders, and social impact leaders assess whether their AI practices are truly equitable and community-centered. The framework reflects how the AI Equity Project has matured: from documenting what is happening across the sector to offering a clear structure for responsible AI governance in nonprofits and a stronger path toward justice in the age of AI.
ABOUT
AI EQUITY TOOLKIT
The AI Equity Project remains a multi-year research initiative focused on how nonprofits and the broader social sector are experiencing, adopting, and questioning AI. Over the past three years, that research has surfaced consistent patterns around trust, governance, power, access, and accountability. This year, the project continues that research while expanding what it produces: not only a new insights report, but also a practical toolkit designed to help organizations apply the learning in real time. The result is an AI Equity Toolkit that sits alongside the research, including the AI Equity Checklist for Fundraisers and AI Equity Workbooks for nonprofits, foundations, and tech companies.
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This evolution reflects what the project has learned: the sector does not only need more evidence about what is happening with AI — it also needs useful tools to respond. The checklist and workbooks are grounded in the same research foundation as the report, but they are designed for action: to help organizations ask better questions, examine risks and power dynamics, and make more thoughtful, transparent, and community-centered decisions about AI. In that way, the AI Equity Project is still doing what it has always done — researching the realities of AI in the sector — while now also turning those findings into tools people can use.
