Don’t Fall Into the Nonprofit AI Adoption Divide

A gap is emerging between nonprofits that are adapting to artificial intelligence (AI) to reimagine how they advance their missions and those that are using it in an ad hoc way and falling behind the curve. That gap can have broader implications on how organizations remain relevant as AI becomes embedded across nearly every sphere of life.

For nonprofits, AI can redefine what impact looks like, and forward-thinking organizations are harnessing it to drive meaningful change. They see AI as not just another tool, but as a shift in how work gets done, and more importantly, in what kind of work is even possible. This shift demands new skills, new ways of working, and a willingness to rethink long-standing assumptions. It also opens the door to extending reach, deepening impact, and responding to needs in ways that were previously out of reach.

What Full AI Adoption Looks Like

That shift is already underway, and the distance between organizations on either side of the AI adoption gap is beginning to widen. Here’s what transformation looks like — not just more efficiency for individuals using AI tools, but increased organizational impact.

HonestReporting used to rely on manual review to identify bias in media coverage — a slow, reactive process limited by staff time. Today, the organization uses AI to analyze content from more than 100 publications in real time, identify patterns of bias, generate sector-wide insight about how narratives spread, and provide tools to help people spot media bias themselves. This is not incremental change, it’s a different operating model.

United Hatzalah in Israel was founded on the premise of rethinking emergency response itself, building a nationwide network of volunteer medics who reach patients within minutes. Now, the organization is layering AI onto its dispatch system to predict where emergencies are likely to occur and position responders in advance. The shift from reacting to crises to anticipating them is resulting in more lives saved.

Most Nonprofits Are Using AI Shallowly

Across the sector, AI adoption is happening, but it remains limited in scope. Nonprofits report using AI primarily for internal productivity — drafting emails, summarizing meetings, refining grant proposals, and supporting communications. According to The Center for Effective Philanthropy’s “AI With Purpose: How Foundations and Nonprofits Are Thinking About and Using Artificial Intelligence,” nearly two-thirds of nonprofits are already using AI for fundraising and development tasks.

Common use cases from Virtuous’ “Nonprofit AI Adoption Report” include donor communications and content (62%), marketing and social media (60%), email and creative work (60%), data analysis and reporting (42%), and operations and internal automation (24%).

This activity creates the appearance of progress, but structurally, very little has changed in how organizations advance their missions. AI is being used as a layer on top of existing workflows, not as a force that reshapes them. Only a small fraction of organizations have documented, repeatable systems for using AI in a coordinated way. In practice, most AI adoption is happening at the individual level — staff experimenting with tools — rather than through systems designated to fundamentally change how the organization works.

The AI Divide

A clear divide is emerging. On one side are organizations using AI to improve efficiency — writing faster emails, generating more content, and saving time on routine tasks. On the other side are organizations using AI to rethink how work gets done and how their missions are delivered.

The Virtuous report makes this explicit:

• 65% describe reactive, individual AI use.
• 18% describe operational use of AI with shared workflows.
• 7% describe strategic use of Ai embedded in goals and planning.

This same pattern is playing out in the private sector. Deloitte reports that while many organizations are still focused on efficiency gains, a smaller group is beginning to redesign business models, offerings, roles, and workflows around AI. A quarter of leaders now say AI is having a “transformative effect” on their organizations — more than double the figure from the prior year.

“Leading organizations are rethinking how work gets done, how teams are structured, and how human and machine capabilities can complement one another in everyday operations,” researchers wrote.

What’s Holding Nonprofits Back

Since AI tools are widely available, the constraints are not access to technology — they are organizational. Research from The Center for Effective Philanthropy and others point to three types of barriers:

• Lack of internal expertise.
• Lack of time and capacity to experiment.
• Lack of clarity on where AI fits into their organization.

Leadership teams understand that AI matters, but they lack a clear path forward. Staff is already stretched thin, and AI is often treated as an efficiency task rather than a strategic lever. Fear, privacy concerns, and ethical considerations also play a role.

Funding dynamics reinforce the problem. From 2018 to 2023, U.S. foundations allocated hundreds of millions of dollars to AI-related efforts, with a significant portion directed toward governance and policy rather than operational capacity.

Given the sector’s generally risk-averse posture and slower pace of tech adoption, support for building internal AI capability remains limited. What’s emerging is a split, with widespread experimentation on one side, and real integration and acceleration on the other.

The Missed Opportunity

The organizations pulling ahead are not using AI more often. They are using it differently — applying it to core mission challenges such as identifying a need before it becomes visible, filling critical data gaps, and expanding access to services.

This is where AI shifts from being a convenience to being a structural advantage. 

If AI remains a side tool, it will produce marginal gains. If it becomes part of the strategy, it will change how impact is created.

Across research from Deloitte, The Center for Effective Philanthropy, and The Bridgespan Group, organizations that move beyond surface-level adoption tend to make three shifts: 

1. From tool to capability. AI is not treated as a set of prompts, but as a way to redesign how work happens.
2. From experimentation to capacity. Organizations invest not just in training, but in ownership, time, and leadership alignment.
3. From tasks to mission-level use cases. They start with the most important problems they are seeking to solve as an organization, not the easiest applications of AI.

Where to Start

Fortunately, more organizations are moving ahead in their AI journeys. The Bridgespan Group outlines a practical path forward: Link AI efforts directly to your mission and ambitions to scale, assess your current technology capacity, strengthen leadership ownership of your technology strategy, partner where internal expertise is limited, build a tech‑literate culture, and develop a clear roadmap for implementation.

AI efforts need to start at the top of the organization. The board and executive leadership need to be driving the conversation forward, both fostering imagination around AI’s potential and providing the guardrails to guide its responsible deployment. 

The value of technology is only as useful as it is adopted. Just as organizations sought to close the digital divide in society, we now need to ensure that the AI gap doesn’t disenfranchise most of the nonprofit sector. The path forward may be complex, but it is not one that nonprofits have to navigate alone.

The preceding content was provided by a contributor unaffiliated with NonProfit PRO. The views expressed within may not directly reflect the thoughts or opinions of the staff of NonProfit PRO.