7 AI stats nonprofit & funder leaders should know

Curious about AI use in the social impact space? New data reveals how nonprofits and funders are finding their footing with AI and what’s needed to move forward with confidence.

Social good leaders can’t ignore this AI moment

AI is no longer a far-off concept. It’s here and being used to shape how nonprofits operate and how funders make decisions. Across the sector, organizations are experimenting with AI as part of a broader nonprofit digital transformation, using it to streamline work, surface insights, and stretch limited resources further. But while adoption is accelerating, confidence isn’t always keeping pace.

To understand what’s really happening on the ground, Bonterra surveyed 547 nonprofit leaders and 300 funders to learn how they’re adopting AI, what’s holding them back, and what they need to move forward responsibly. The result is “The AI Readiness Path,” a data-driven look at AI in social impact — not in theory but in practice.

Below are seven of the most eye-opening stats from the research. Together, they reveal where nonprofits and funders are aligned, where friction remains, and what it will take to turn AI momentum into meaningful progress.

1. 69% of nonprofits are already using AI.

AI is no longer experimental in nonprofit work. Most organizations have already introduced it into their day-to-day operations, whether through fundraising, communications, reporting, or administrative tasks.

At the same time, adoption has often outpaced strategy. Many nonprofits are using AI tools tactically without a long-term plan for governance, integration, or measurement.

Why it matters: Early adoption creates real opportunity. But without guardrails, it can also introduce risk. The strongest nonprofit technology trends point toward connected systems and clear standards — not disconnected tools layered on top of already-busy teams.

2. 92% of nonprofits are concerned about how AI uses their data.

One theme that pops up across the entire report is trust. Nearly all nonprofit respondents expressed concern about how AI tools handle sensitive information, from donor data to deeply personal client stories.

These concerns aren’t theoretical. For organizations built on trust and accountability, uncertainty around data use can slow or even halt deeper adoption.

Why it matters: Without transparency and clarity, confidence in AI stalls. For nonprofits to move forward, they need tools that prioritize privacy, explainability, and ethical data practices from the start.

3. Nearly half of nonprofits cite time and staffing as major barriers to AI adoption.

While AI is often framed as a time-saver, many nonprofits say the opposite is true, at least at first. Learning new tools, integrating them into existing workflows, and training staff takes time that already-stretched teams don’t have.

Some respondents also described AI tools as “too expensive” or “unclear in value,” especially when systems don’t work well together.

Why it matters: Time saved only matters if it can be reinvested into mission delivery. Fragmented tools and steep learning curves can negate AI’s promised efficiency.

This is where resources like Bonterra Que come in. Built directly into the tools nonprofits already use, Bonterra Que acts like an embedded teammate, helping teams analyze data, surface insights, and take action without adding new platforms or complexity. Que was made to support fundraising work, not create more of it. Designed specifically for social good, Que prioritizes trust, transparency, and human judgment, making it the most trusted AI platform for nonprofits and funders.

4. 40% of funders worry about over-reliance on automation.

Funders are optimistic about AI’s potential, but they are also cautious. A significant number worry that automation could replace human judgment in areas where nuance and context matter most. As one perspective in the report makes clear, AI should support people, not sideline them.

Why it matters: Responsible AI must enhance expertise, not replace it. Funders want systems that provide insight and recommendations, while keeping humans firmly in control of decisions.

5. 30% of funders cite legal and regulatory requirements as a top AI challenge.

For funders, AI adoption is not just a technology decision. It’s a compliance decision. Legal, regulatory, and governance considerations are a real barrier, especially in high-stakes environments like grantmaking and corporate social responsibility programs.

Why it matters: Funders need clarity on how AI fits within existing rules and reporting requirements. Without clear guidance, even well-intentioned AI use can involve unnecessary risk, making compliance readiness a critical factor in adoption decisions.

6. Only about half of funders consider AI-generated proposals fully ethical.

AI-assisted grant proposals sit at the center of a growing ethical debate. While funders see the efficiency gains, many remain uneasy about fairness, authenticity, and disclosure. This hesitation signals that expectations are shifting, not shutting down.

Why it matters: Clear disclosure and human oversight in AI systems will be critical to building confidence around AI-assisted proposals. As norms evolve, transparency will increasingly become table stakes for nonprofits seeking funding.

7. 93% of funders say employee training is the best way to build trust in AI.

When it comes to trust, funders are nearly unanimous: training matters more than automation alone. People are more confident in AI when they understand how it works, when to use it, and where human judgment is required. Education, not speed, is what turns AI into a trusted tool.

Why it matters: Education reinforces accountability, prevents misuse, and strengthens AI trust and transparency. With training in place, teams can ensure they are using AI responsibly.

How Bonterra is responding

The findings point to a clear conclusion. AI readiness is not about adoption alone. It is about trust, clarity, and connection across the social good ecosystem.

Bonterra’s approach to AI reflects that reality. Every AI capability, including Bonterra Que, is built on three pillars:

• Governance and ethics, with human oversight at every stage
• Privacy and security, so client data is protected and never used to train large language models
• Environmental sustainability, with efficient, responsible deployment by design

By connecting engagement, fundraising, and intelligence in one ecosystem, Bonterra helps nonprofits and funders move forward with confidence, not guesswork.

Ready to go deeper?

Explore “The AI Readiness Path” to see what nonprofits and funders across the sector really think about AI, and how the right nonprofit software can turn AI potential into real-world impact.