AI Considerations for Nonprofits
What’s happening: AI is becoming more visible across the nonprofit sector, prompting organizations to evaluate where it may support mission-driven work.
Why it matters: Foundations invested $300 million in AI initiatives from 2018 to 2023—with one-third focused on governance and ethics1—and 61 percent of nonprofits now use AI for fundraising and development tasks.1
What to know now: While AI is not essential for every nonprofit, understanding its potential applications can help leaders make thoughtful and strategic decisions about whether and how to explore it.
Potential Applications in Fundraising and Donor Engagement
What AI can do:
• Analyze donor engagement patterns
• Predict which supporters may give again
• Inform personalized outreach strategies
What the data shows:
• AI-enabled campaigns reached goals 33 percent faster due to better targeting and timing.2
• In one case, AI tools predicted donor renewal with 86 percent accuracy.2
• Recurring gifts rose up to 264 percent when organizations used AI supported personalization.4
The takeaway: AI can accelerate fundraising progress and stretch limited development capacity. However, it should not replace the real-world relationships that drive philanthropy. It can simply help direct staff attention where it can be most effective. AI tools may be useful where teams are stretched and data exists, but suitability depends on culture, strategy, and staff capacity to act on insights.
Streamlining Administrative and Operational Processes
AI may also help to ease administrative burden, freeing time for more mission-critical work.
Where AI helps:
• Organizing information
• Summarizing reports
• Supporting compliance documentation
• Reducing repetitive, time-consuming tasks
Real-world example: Houston Endowment’s AI-powered, oral reporting pilot cut grantee administrative time by 75 percent and improved feedback.3
How to evaluate fit:
• Identify bottlenecks or repetitive tasks
• Assess whether they are data-heavy or ripe for automation
• Consider alignment with operational goals and available capacity
Enhancing Program Analysis and Decision-Making
AI can enable rapid analysis of large data sets to identify trends, forecast needs, or assess risks. In one example, during the 2023 Sudan conflict, Mercy Corps used AI to analyze 10 years of satellite data, identify famine risk zones, and deploy aid preemptively.2
Important considerations:
• AI insights are only as reliable as the underlying data
• Staff expertise is essential for interpreting outputs
• Data governance and quality must be strong
Could it help your organization? Maybe. AI can strengthen data-driven decision-making, especially when timeliness matters, but its use requires solid data practices and analytical capacity.
Readiness, Training, and Ethical Considerations
Current state:
• 68 percent of nonprofits want staff training before adopting AI.1
• By late 2025, 73 percent had no AI policies in place.5
Why governance matters:
• Protects sensitive information
• Ensures alignment with organizational values
• Builds transparency and equity
• Addresses privacy, bias, and accountability concerns
In other words,AI readiness requires training, digital literacy, and responsible governance.
Planning Thoughtfully and Moving at the Right Pace
Remember: AI adoption isn’t all-or-nothing. Organizations can start small by identifying specific pain points or opportunities.
Potential questions to ask your team:
• Which activities regularly require significant manual effort?
• What insights would strengthen decision-making?
• What data governance structures exist—and what’s missing?
• How might AI complement (not replace) human relationships?
• What training or capacity building is needed for responsible use?
The punchline: A cautious, intentional approach to AI implementation allows organizations to evaluate benefits and risks without pressure. AI may offer meaningful support for some, but it should only be adopted when it advances the mission and strengthens the team.
Sources:
1“AI with Purpose: How Foundations and Nonprofits Are Thinking About and Using Artificial Intelligence,” The Center for Effective Philanthropy
2 “Machine Learning for Nonprofit Organizations.” Journal of Nonprofit Innovation
3 “Pilot Project Centers Grantee Voice through Oral Reporting and AI,” Houston Endowment
4 “How AI Can Deepen Nonprofit Relationships,” Stanford Social Innovation Review
5 “Grassroots and Non-Profit Perspectives on Generative AI,” Joseph Rowntree Foundation
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