Where to use AI in your nonprofit (and where you shouldn’t)

The smartest nonprofit leaders aren’t asking “Should we use Artificial Intelligence?” They’re asking, “What must stay human?”

If you’re feeling uncertain about AI, you’re not alone. Recent research shows 92% of nonprofits feel unprepared for AI implementation, 60% express uncertainty and mistrust, and 76% don’t even have an AI policy in place.

But here’s what’s also true:

The nonprofits gaining ground right now aren’t the ones using AI for everything; they’re the ones who’ve figured out exactly where to draw the line.

This guide will help you make those decisions strategically.

Where AI can (and should) help your nonprofit

Let’s start with the good news: Artificial Intelligence can save your team significant time and money when used in the right places.

Here’s where nonprofits are seeing real results:

1. Data analysis and donor insights

AI excels at finding patterns humans would miss. The American Cancer Society achieved a 400% increase in donation conversion rates by using machine learning to optimize its communication channels and messaging. HIAS used AI to predict email appeal effectiveness and saw a 230% increase in donations.

Use AI to:

• Analyze donor databases to reveal giving patterns and lapse risk
• Predict which communication channels work best for different donor segments
• Identify at-risk donors before they lapse (Greenpeace retained 64 donors who would have lapsed, saving over $23,000)
• Optimize direct mail targeting (Parkinson’s UK saw a 23% revenue increase using AI segmentation)

2. Repetitive administrative tasks

This is where AI really shines: handling high-volume, low-complexity work that drains your team’s time.

Use AI to:

• Draft initial thank-you emails (that humans then personalize)
• Handle routine data entry and database updates
• Schedule meetings and manage calendars
• Answer frequently asked questions through chatbots
• Research grant opportunities and compile application requirements

3. Content creation support (with oversight)

AI can help you work faster, but it should never be the final voice of your organization.

Use AI to:

• Generate first drafts of newsletters, blog posts, or social media content
• Brainstorm campaign themes and messaging angles
• Create initial grant proposal outlines
• Personalize donation appeals at scale (then have humans review)

Where AI should never replace humans

Here’s where AI falls short and where your organization’s humanity becomes your competitive advantage.

1. Final-draft communications and authentic storytelling

Generic AI-generated content makes organizations blend into the noise. Donors connect with your specific mission and unique approach. AI can’t capture lived experience.

People give because they feel something.

AI can analyze emotions, but it can’t genuinely express them. Your stories about the people you serve, the challenges you overcome, the victories you celebrate? Those require human understanding and care.

Keep human:

• Final versions of all external communications
• Personal narratives and beneficiary stories
• Annual reports and impact statements
• Any communication representing someone else’s experience

2. Major donor relationships and sensitive situations

High-touch relationships require the ability to read the room, demonstrate genuine empathy, and make real-time judgment calls. AI can’t do any of that.

Keep human:

• Major donor cultivation and stewardship
• Crisis communications
• Conflict resolution
• Sensitive situations that require empathy and accountability

3. Strategic decision-making and direct services

AI can analyze data and surface trends. It cannot make value judgments. It cannot understand the full context of your mission, community needs, or organizational culture.

Keep human:

• Strategic planning and organizational decisions
• Program design and adaptation
• Direct services to vulnerable populations
• Any situation where human dignity and understanding are paramount

How to actually start using AI: a practical framework

Here’s your roadmap:

Step 1: Map your high-volume, low-complexity tasks

Spend one week tracking where your team spends time on:

• Repetitive administrative work
• Data entry and organization
• First drafts that get heavily edited anyway
• Research and information gathering

These are your AI opportunities.

Step 2: Start with one low-risk pilot

Don’t try to transform everything at once. Pick one specific use case:

• Summarize meeting notes
• Draft job descriptions for open positions
• Generate newsletter topic ideas

Run it for 30 days. Measure time saved. Evaluate quality. Adjust.

Step 3: Build your AI policy and guardrails

Your policy should address:

Data privacy and security (70% of nonprofits’ top concern):

• Never upload donor lists or sensitive beneficiary data to public AI tools
• Understand that many AI platforms retain data for training
• Use privacy-focused tools or enterprise versions with data protections

Accuracy and fact-checking (63% of nonprofits’ concern):

• AI makes mistakes. Always verify facts and statistics
• Be aware that AI can misinterpret context (like mistaking April Fool’s posts for fact)
• Never publish AI-generated content without human review

Transparency and disclosure:

• Only 15% of nonprofits currently disclose AI use. Be transparent.
• Decide when and how you’ll disclose AI assistance
• Consider noting “AI-assisted” on applicable content

Step 4: Apply the 10-80-10 rule

A useful framework from AI practitioners:

• 10% human strategy: Define the goal, provide context, set parameters
• 80% AI execution: Let AI do the heavy lifting
• 10% human refinement: Edit, personalize, add authenticity

The simple test: Should this task use AI?

Before implementing any AI tool, ask yourself three questions:

1. Does this improve human connection or replace it?

If AI helps you reach more people with personalized messages, that improves connection. If it replaces the personal touch that makes donors feel valued, it undermines your mission.

2. Does it free people to do more meaningful work?

AI that handles data entry so your team can focus on relationship-building? Yes. AI that makes strategic decisions that your team should own? No.

3. Will stakeholders feel more valued or less valued as a result?

This is the ultimate test. Your donors, volunteers, beneficiaries, and community partners should feel that technology is enhancing, not diminishing, their relationship with your organization.

Keep humans at the center

Use Artificial Intelligence strategically to amplify your impact: Automate routine tasks, analyze data more effectively, and reach more people with your message. But recognize AI’s limitations and protect the human elements that make your work meaningful.

Your nonprofit’s greatest asset will always be the people who care about your mission: your staff, volunteers, donors, board members, and the communities you serve. Use technology to support them, never to replace them.

The future of nonprofit work isn’t in choosing between humans and AI.

It’s using AI wisely so that humans can focus on what they do best: building relationships, making ethical choices, and changing lives.

Key takeaways

• Start small: Pick one low-risk pilot project and run it for 30 days
• Create an AI policy: Address data privacy, accuracy, and transparency
• Use AI for: Repetitive tasks, first drafts
• Keep human: Final communications, major donor relationships, strategic decisions, direct services
• Apply the 10-80-10 rule: Human strategy, AI execution, human refinement
• Always ask: Does this improve connection, free up meaningful work, and make stakeholders feel valued?

Frequently asked questions about AI for nonprofits

Q: What’s the best AI tool for nonprofits to start with?

A: ChatGPT (free version) or Microsoft Copilot are the easiest starting points. They’re low-cost, don’t require technical expertise, and can handle most basic tasks like drafting content, brainstorming ideas, or summarizing documents. Start with one specific use case, like summarizing public meeting notes, before expanding.

Q: Is it safe to use Artificial Intelligence with donor data?

A: Not with public AI tools like ChatGPT’s free version. Never upload donor lists, financial information, or personally identifiable information to public AI platforms. Many retain data for training purposes. If you need AI for donor analysis, use enterprise tools with data protection agreements, or work with vendors who specialize in nonprofit CRM systems with built-in AI features.

Q: Do we need to tell donors when we use AI?

A: There’s no legal requirement, but transparency builds trust. Currently, only 15% of nonprofits disclose AI use. At the very least, include your AI policy in your website’s transparency section. The key is ensuring AI-generated content is always reviewed and personalized by humans before it reaches donors.

Q: How much does AI cost for nonprofits?

A: You can start for free. ChatGPT and Microsoft Copilot offer free tiers that handle most basic needs. Paid versions (ChatGPT Plus at $20/month, Copilot Pro at $20/month) add more features. Specialized nonprofit AI tools for donor management or fundraising typically range from $50-$500/month, depending on your database size. Start free, then upgrade only when you’ve proved the value.

Q: Can AI replace our nonprofit marketing agency or consultant?

A: No. AI cannot replace the strategic thinking, creative expertise, and human judgment that agencies bring. AI is a tool that helps with execution: drafting content, analyzing data, and automating tasks. But it can’t understand your mission deeply, make strategic decisions, build authentic relationships, or know when to break the rules creatively. Think of AI as a supplement to professional expertise, not a replacement.

Q: What are the biggest mistakes nonprofits make with AI?

A: The three most common mistakes are: (1) Publishing AI-generated content without human review. AI makes factual errors and lacks an authentic voice; (2) Uploading sensitive donor or beneficiary data to public AI tools. This is a major privacy risk, and (3) Using AI for high-touch relationships like major donor cultivation. These require genuine human empathy and judgment that AI can’t replicate.

Q: How do we create an AI policy for our nonprofit?

A: Start with three key areas: (1) Data privacy: What information can and cannot be shared with AI tools, (2) Quality control: Who reviews AI output before it goes public, and (3) Disclosure: When and how you’ll tell stakeholders about AI use. You don’t need a 50-page document. A simple one-page policy covering these basics protects your organization and gives staff clear guidelines.

Q: Will AI take jobs away from nonprofit staff?

A: AI should free up staff for more meaningful work, not replace them. The goal is to automate repetitive tasks (data entry, first drafts, scheduling) so your team can focus on relationship-building, strategic thinking, and direct service delivery. Organizations using AI effectively report staff spending more time on mission-critical work that requires human judgment and empathy.

Sources and resources

GivingTuesday. “AI Readiness and Adoption in the Nonprofit Sector in 2024: Results from GivingTuesday’s AI Readiness Survey.” Research showing 92% of nonprofits feel unprepared for AI implementation and documenting key barriers to adoption.

GoBeyond.AI. “How American Cancer Society Uses AI to Boost Fundraising Effectiveness.” Case study documenting a 400% increase in donation conversion rates through machine learning optimization of communication channels and messaging.

Dataro. “Artificial Intelligence for Nonprofits: Complete Explainer.” Case studies documenting Parkinson’s UK’s 23% revenue increase from AI segmentation (14% vs 9% response rate) and Greenpeace’s retention of 64 at-risk donors, saving an estimated $23,040.

CCS Fundraising. “AI in Fundraising: A Comprehensive Guide.” Industry research and best practices for implementing AI in nonprofit fundraising, including data analytics applications and donor engagement strategies.

Stanford Social Innovation Review. Barenblat, K., & Gosselink, B. H. “Mapping the Landscape of AI-Powered Nonprofits.” Analysis of how nonprofits across sectors are deploying AI for operations, fundraising, and program delivery.

DonorSearch. “AI for Nonprofits: Everything Your Org Needs to Know.” Research showing 58% of nonprofits use AI for communications and 68% for data analysis, plus implementation frameworks and best practices.

Additional case studies. Success stories from HIAS, Parkinson’s UK, and Greenpeace are drawn from industry reports and presentations by nonprofit fundraising consultants. These represent documented results from organizations using AI for donor segmentation, email optimization, and retention strategies.

AI ethics and best practices. Data privacy concerns, implementation frameworks (including the 10-80-10 rule), and policy recommendations are synthesized from multiple sources, including the Nonprofit Technology Network (NTEN), TechSoup, and nonprofit AI practitioners.

This article was written and edited by Counterintuity, with AI-assisted brainstorming, research, and SEO optimization.