Where AI Agents Fit in Nonprofit Workflows (And Where They Don’t)

Nonprofits run lean. Between donor stewardship, grant reporting, program delivery, fundraising, and communications, most teams are doing the work of three organizations with the budget of one. A 2025 Urban Institute survey found that 72% of nonprofits cite budget constraints as among the most critical factors affecting their ability to hire and retain staff, and reported staff burnout nearly doubled year over year. It’s no surprise that AI agents are increasingly showing up in that conversation, positioned as a way to help stretched teams get more done without adding headcount.

It’s a reasonable instinct to pause here, to wonder what more capable AI means for the people already doing this work. The short answer is that agents are most valuable when they’re doing the things your team doesn’t have enough time for, not the things only your team can do.

If your team is still figuring out where AI fits—or whether you’re ready for it at all—many organizations are right there with you. This post is designed exactly for that moment. Let’s build a clearer picture of what agents actually do so you can make that call with confidence.

What’s an AI Agent, Exactly?

Most people first experience AI in a chatbot: ask a question, get an answer. Agents go further. Researchers at MIT Sloan define agentic AI as “autonomous software systems that perceive, reason, and act in digital environments to achieve goals.” The key word is “act.”

A chatbot answers your question about grant deadlines. An AI agent can search your grant calendar, flag the three most urgent ones, draft a status update for your program officer, and queue it for your review—all from a single prompt. Defining characteristics include:

• Uses tools; searching databases, drafting content, triggering workflows
• Operates over multiple steps, not just a single response
• Adapts when something doesn’t go as planned
• Hands off to a human when judgment or relationship is required

Where Agents Show Up in Nonprofit Work

Awareness of AI in the sector is high. A 2025 TechSoup benchmark report found 96% of nonprofits have a basic understanding of what AI can do. But 76% still lack a formal strategy, and only about a quarter are using it for tasks like grant writing. Agents are one of the ways organizations are starting to close that gap.

We’re using the Development Agent to accelerate donor connections and make those connections more impactful in a shorter period of time. This will help us accelerate fundraising across all giving levels.

Brian Otis
Vice President for University Advancement

Donor Development and Fundraising

Agents can research prospects, compile giving histories, and conduct individualized, brand-aligned outreach at a scale a fundraising team could never manage alone. Blackbaud’s Development Agent is a purpose-built example, designed specifically for the nonprofit context with the data integrations and sector knowledge this work demands. One important note regardless of which tool you use: constituents should know when they’re hearing from an AI-assisted system. Transparent disclosure isn’t just an ethical standard; it protects the donor relationships your team has worked to build.

Grants and Reporting

Agents can pull narrative elements from past reports, surface program data, and draft initial language for renewal applications—handling the gathering and structuring so your team can focus on the story.

Communications and Content

From newsletter drafts to board updates, agents can generate first drafts based on your existing materials and voice, research topics, and help you stay consistent with your editorial calendar.

Operations and Administration

Meeting prep, data cleanup, document summaries, email triage—agents can take on the administrative work that quietly consumes hours each week. This is often where nonprofits find the fastest return early in their AI journey.

What AI Agents Don’t Do

This part matters as much as the capabilities. AI agents aren’t human decision-makers. The judgment calls that shape your mission and relationships belong to your people. It’s important to remember these limitations:

• Security, trust, and transparency are fair questions to demand answers to. Where does constituent data go? Will donors know they’re interacting with an AI-assisted system? What guardrails prevent the agent from saying something off-brand or inaccurate? These are the right questions to ask of any agent you consider. How clearly they’re answered tells you as much about the tool as any feature list.
• They extend relationship—they don’t replace it. Agents can maintain consistent, personalized touchpoints at a scale your team can’t match alone. What they don’t substitute is your judgment about when a conversation needs to go deeper, or the weight of a personal ask from someone who truly knows the donor.
• The agent is only as strong as the data behind it. If your donor records are reasonably complete and current, the agent will perform to the same degree. The cleaner and more consistent your data, the sharper the outreach and the better the results. Investing in data quality isn’t a separate project. It actually raises the ceiling on what your agent can do.
• They work best with smart escalation, not constant supervision. Once an agent is properly configured with the appropriate context and guardrails, it should be able to run effectively. What matters is building in the right triggers: clear mechanisms that surface edge cases, unusual situations, or high-stakes moments that genuinely need a human in the loop. Trust the agent to handle the routine; stay close to what matters most.
• Access is not the same as a strategy. A 2025 PwC survey found that while 66% of early AI agent adopters report increased productivity, fewer than half have rethought their operating models. Getting real value means connecting agents to your workflows, building team fluency, and deciding in advance who owns reviewing and acting on what the agent surfaces.

The Right Approach for Getting Started

The nonprofits seeing the most traction aren’t trying to automate everything at once—they’re starting with the highest-impact use cases and building confidence from there. That said, purpose-built agents designed for specific workflows can dramatically lower the barrier to entry. When an agent is already configured for your context, your data, your constituents, your goals, you don’t need to be an AI expert to get started. Learning happens through use, not before it.

The AI Coalition for Social Impact offers a free AI certification designed for the nonprofit sector. It’s a useful resource for teams that want to build broader AI fluency alongside implementation. You can join the waitlist now to be notified when registration opens.

AI agents won’t solve all the resource constraints that define so much of nonprofit life. But for teams that are already stretched, agents can be the difference between what’s possible today and what’s been sitting on the to-do list for months.

That’s not a small thing.