AI for nonprofits: FAQ
What is AI for nonprofits?
AI technology refers to machine learning tools that process and analyze data to either identify trends and patterns or recreate similar content. AI is present in many aspects of life, even before the popularization of tools like ChatGPT. For instance, your smartphone uses AI to power digital assistants like Siri.
That said, it’s important to distinguish between the various types of AI because they work in distinct ways. Here are the most common types of AI nonprofits should know:
- Generative AI is the type of AI that has dominated recent headlines and has universal uses, even in life outside of the office. Generative AI creates new content—text, images, code, or video—based on patterns it has learned from existing data. ChatGPT and Gemini are generative tools.
- Predictive AI is the type of AI that is valuable for data analysis and trend forecasting. While less flashy than generative AI, predictive AI is best for big-picture nonprofit strategizing. For nonprofits, predictive AI might score donors based on their likelihood to give, identify at-risk recurring donors, or project future campaign revenue.
- Conversational AI is the type of AI that uses natural language processing, which gives machines the ability to understand, interpret, and respond to human language in a meaningful way. In other words, it bridges the gap between how humans communicate and how computers understand. This might look like an automatic chatbot built into your homepage that improves user experience.
Regardless of the type of AI, it is likely powered by machine learning. Machine learning is the specific subset of AI where computers “learn” from data without being explicitly programmed for every rule. The more data you feed it, the more accurate it becomes over time. This might look like a spam filter that gets better at blocking junk mail the more you mark items as “spam,” or a donation form that learns which suggested ask amounts yield the highest conversion rates.
AI vs. automation in a nonprofit context
Automation refers to using technology to handle repetitive, rule-based tasks without human intervention—think automating donation receipts or syncing data between your CRM and email platform. It’s about efficiency and consistency, reducing manual work so staff can focus on higher-value activities. AI, on the other hand, goes beyond rules—it learns, predicts, and adapts. It can analyze patterns in donor behavior to forecast giving trends, for example.
What do nonprofits use AI for?
Your current nonprofit tech stack likely leverages AI already, even if it’s just in the background. Here’s a breakdown of AI-powered features that different types of nonprofit software use:
Fundraising and donor management platforms
- Predictive donor scoring to identify high-value prospects and their likelihood to give.
- Automated suggestions for next-best actions or specific ask amounts.
- Speech-to-text transcription that automatically logs donor call notes into the CRM.
- Wealth screening integration that updates donor capacity in real-time.
Marketing and communications tools
- Generative content drafting for social media captions, blog posts, and newsletters.
- Subject line optimization and send-time prediction to maximize open rates.
- Dynamic audience segmentation that groups supporters based on behavioral signals.
- Image generation to create royalty-free visuals for campaigns without a graphic designer.
Program and service delivery software
- Case management alerts that flag at-risk clients based on service usage patterns.
- Automated volunteer matching that pairs skills and availability with open shifts.
- Outcome analysis that reads unstructured text (like survey comments) to measure sentiment and impact.
Grant management and strategy
- Automated prospect research that scans databases to match your nonprofit with relevant grant opportunities.
- Proposal drafting assistants that generate first drafts of grant narratives based on your past successful applications.
- Compliance tracking to automatically flag upcoming reporting deadlines and requirements.
Financial and operational management
- Automated expense coding that scans receipts and categorizes expenses without manual entry.
- Fraud detection algorithms that monitor transactions for unusual activity or policy violations.
- Contract review tools that quickly summarize key terms and flag risks in vendor agreements.
Data and analytics platforms
- AI-powered dashboards highlighting anomalies or trends
- Predictive modeling for campaign or program outcomes or future financial health
- Data hygiene tools that organize data and remove duplicates
Accessibility and inclusion
- Real-time captioning and translation for virtual events and webinars.
- Automated alt-text generation to ensure website images are accessible to visually impaired users.
- Bias detection in job descriptions or communications to ensure inclusive language.
Support and engagement tools
- 24/7 chatbots to answer common supporter questions instantly.
- Virtual event assistants that handle registration inquiries and schedule changes automatically.
Why should nonprofits start preparing for AI now?
As AI-powered tools become more accessible and advanced, AI adoption shows no sign of slowing down. By becoming AI-literate, you can:
- Help your organization find efficiency gains. With AI automating routine tasks and supplementing teams with generative content, your colleagues will have more time for higher-level work.
- Future-proof your career and organization. With the high rates of AI adoption in the sector, understanding AI ensures you don’t fall behind as these tools become the standard for fundraising and operations.
- Make safer, more ethical decisions. Proactively learning about AI allows you to identify risks—like data privacy issues or bias—before they become costly liabilities for your organization.
- Spot opportunities others miss. When you understand how AI really works, you start seeing specific, practical ways it can solve your unique operational bottlenecks.
- Lead the conversation with confidence. Whether talking to your board, your donors, or your tech vendors, being informed allows you to ask the right questions and evaluate tools based on value, not hype.
Even if you aren’t ready for widespread AI integration just yet, proactively addressing it and educating your staff helps prevent costly missteps. For instance, without clear guidelines, staff might start independently experimenting with free AI tools in ways that expose sensitive donor data or create compliance risks. By setting policies early and mapping out where AI could add value, your nonprofit can explore opportunities safely and strategically, rather than scrambling to fix problems after they occur.
How to get started with AI for nonprofits
