From Curiosity to Commitment: How Nonprofits Are Using AI in 2026 and What Has Changed in the Last Year

A year ago, most nonprofits were cautiously experimenting with artificial intelligence. Staff members were quietly using ChatGPT to draft fundraising emails. Development directors were testing AI tools on the side, often without formal guidance or organizational buy-in. The conversation across the sector was largely theoretical: Could AI help nonprofits? Should nonprofits use it?

That conversation has shifted dramatically. According to the 2025 State of AI in Nonprofits Report from TechSoup and Tapp Network, which surveyed more than 1,300 nonprofit professionals, 85.6% of organizations are now actively exploring AI tools. Nonprofit Tech for Good reports that 82% of nonprofits use AI informally, primarily for content generation like drafting donor emails and marketing materials. And the Center for Effective Philanthropy's AI With Purpose report, based on surveys of 215 foundations and 451 nonprofits, confirms that the nonprofit sector's AI adoption trajectory now mirrors the business world, where usage surged from 55% in 2023 to nearly 80% in 2025.

The question is no longer if nonprofits should adopt AI. The question is how to do it well.

What Changed in the Last Year

The most striking shift has been the move from individual experimentation to organizational conversation. In early 2025, most nonprofit AI use was informal and ad hoc. Staff members were testing tools independently, often without their organization's knowledge. Fast forward to today, and AI has become a standing topic in board meetings, strategic planning sessions, and team check-ins.

Fast Forward's 2025 AI for Humanity Report captured this acceleration vividly. In 2024, only 13 of 247 applicants to Fast Forward's accelerator identified as AI-powered. By 2025, that number jumped to nearly half, and in 2026 it more than doubled again to 379 of 782. Kevin Barenblat, co-founder of Fast Forward, described the pace as "an incredible transformation" in how quickly organizations are thinking about incorporating new tools.

Major philanthropic investments have also accelerated the pace. In October 2025, a coalition of 10 leading foundations announced Humanity AI, a $500 million, five-year initiative to ensure people have a stake in AI's future. The participating foundations, including the Ford Foundation, MacArthur Foundation, and Omidyar Network, committed to directing grants toward AI that strengthens communities and protects democratic values.

Meanwhile, the Bridgespan Group noted that this moment represents a wake-up call for the sector. For years, nonprofits have had to forgo technology investments to prioritize direct programmatic work. AI is providing an opportunity to correct that course and build the infrastructure needed to advance social change.

How Nonprofits Are Actually Using AI

The most common applications remain practical and immediate. Nonprofit Tech for Good's 2025 data shows the top three uses for AI chatbots among nonprofits: checking grammar, spelling, and punctuation (53%), brainstorming headlines and subject lines (53%), and creating first drafts of content (39%). These are the kinds of time-saving applications that stretched nonprofit teams need most.

But the uses are expanding. The TechSoup report found that 60% of nonprofit respondents show strong interest in AI for grant writing and fundraising optimization, areas where a well-crafted prompt can save hours of drafting time. Giving USA highlighted specific AI tools gaining traction in the sector, including ChatGPT for research and campaign development, Claude for copywriting, and Canva's Magic Studio for graphic design.

On the fundraising side, the data tells an encouraging story. Nonprofit Tech for Good found that 30% of nonprofits say AI has boosted fundraising revenue in the past 12 months. Even more telling: donors with higher-giving capacity are more supportive of nonprofit AI use, with 30% of high-dollar donors supporting AI adoption compared to 13% of smaller donors.

For organizations focused on donor retention and mid-level giving, a CRM platform that centralizes donor data becomes the foundation that makes AI tools effective. AI can only personalize outreach, predict donor behavior, and identify giving patterns if the underlying data is clean, accessible, and organized in a system designed for nonprofit fundraising.

The Equity Divide Is Widening

AI adoption is not happening evenly across the sector. The TechSoup report revealed that larger nonprofits with annual budgets exceeding $1 million are adopting AI at nearly twice the rate of smaller organizations (66% vs. 34%). Nearly half of nonprofits (43%) rely on just one or two staff members to manage IT or AI decision-making. And 40% of nonprofits report that no one in their organization is educated in AI, according to Google.org.

Interestingly, the Fast Forward report found that the smallest nonprofits building their own AI solutions (budgets under $100,000) actually report the highest percentage of employees using AI regularly, at 82%. Small teams that embrace AI often do so out of necessity, stretching every resource to maximize impact.

The funding challenge remains real. The Chronicle of Philanthropy reported that 84% of AI-powered nonprofits say additional funding is what they need most to continue developing and scaling their tools. Only 4% of nonprofits have AI-specific training budgets. The catch-22 is clear: organizations need capital to prove AI's impact, but they need proven impact to unlock capital.

Where the Sector Goes From Here

As we move into 2026, several trends point to where nonprofit AI adoption is heading. BizTech Magazine reported that nonprofits will expand AI-powered back-office operations like invoice processing. The Chronicle of Philanthropy predicted that 2026 will bring the merger of predictive and generative AI into a single fundraising assistant, enabling what some are calling "precision philanthropy," reaching the right donors with the right message at the right time.

For nonprofits that have not yet started, the research is consistent: begin with what you have. Turn on AI features in existing tools. Identify one or two areas where AI could save the most staff time. Draft an AI use policy, even a simple one. And invest in training, because the gap between organizations that embrace AI strategically and those that do not will only grow wider.

The technology is here. The sector is moving. The opportunity is too significant to wait.