Artificial intelligence has entered the nonprofit sector, but adoption is uneven, informal and often poorly governed.
Many organizations are already using AI to draft fundraising emails, summarize meetings, create social media posts and research grant opportunities. Far fewer have developed an organization-wide strategy, approved tools or clear rules governing sensitive information.
TechSoup’s 2025 benchmark report, based on responses from more than 1,300 nonprofit professionals, found widespread interest in AI across the sector. However, interest should not be confused with mature implementation. Many nonprofits remain in the experimentation stage, where individual employees use public tools without shared standards, reliable internal data or formal oversight.
AI Use Is Growing Faster Than AI Governance
The most common nonprofit AI applications are relatively simple:
- Drafting donor communications
- Creating marketing content
- Summarizing documents
- Brainstorming campaigns
- Researching funding opportunities
- Preparing meeting notes
- Improving basic administrative work
These uses can save time, but they rarely address deeper operational problems.
A nonprofit may generate newsletters faster while employees still cannot find the correct volunteer policy. It may draft grant language with AI while reporting procedures remain scattered across folders and email accounts. It may summarize meetings without preserving the final decisions in an authoritative location.
This creates activity without building organizational capacity.
The 2025 Charity Digital Skills Report found that 69% of charities wanted more guidance on responsible AI adoption. That figure reflects the central problem: employees are moving ahead with AI faster than many organizations can establish policies, training and accountability.
The Biggest Divide Is Organizational Readiness
The important divide is not between nonprofits that use AI and those that do not. It is between organizations that have reliable information systems and those that do not.
AI performs best when it can access accurate, approved and well-organized information. When policies are outdated, procedures conflict or essential knowledge exists only in employee memory, AI simply retrieves uncertainty faster.
Before expanding AI use, nonprofit leaders should ask:
- Which tools are employees already using?
- What information are they entering into those tools?
- Which AI uses have been formally approved?
- Who is responsible for reviewing AI-generated work?
- Where is the organization’s authoritative knowledge stored?
- Can employees identify which policies and procedures are current?
- Are permissions protecting HR, financial, client and board information?
These questions reveal whether AI adoption is controlled or merely happening.
The Strongest Opportunity Is Internal Knowledge
The most valuable nonprofit AI project may not be fundraising or marketing. It may be creating a secure internal system that helps employees and volunteers find approved answers.
A governed knowledge hub can organize policies, training materials, grant requirements, program procedures and leadership decisions. An assistant such as Maisy can then help authorized users retrieve that information through natural-language questions.
This supports faster onboarding, reduces repeated questions and helps organizations retain institutional knowledge when experienced employees leave.
It also creates a stronger foundation for future AI projects. Once information is organized, permissioned and governed, the nonprofit can cautiously expand into workflow assistance, reporting support and other controlled applications.
What Nonprofits Should Do Next
Nonprofit leaders do not need to stop AI experimentation. They need to bring it under management.
Start by documenting current AI use, identifying sensitive risks and selecting one measurable operational problem. Establish approved tools, human-review requirements and clear data rules. Then organize the knowledge required to support the chosen use case.
The objective should not be to adopt as much AI as possible. It should be to create reliable systems that reduce administrative friction, improve consistency and retain institutional knowledge.
Nonprofit AI adoption is real, but the sector is still early. The organizations that benefit most will not be those that experiment with the most tools. They will be those that connect AI to governed information, responsible oversight and clearly defined mission outcomes.
