Artificial Intelligence (AI) has varying degrees of acceptance and use, as is the case with any emerging technology. AI is driving meaningful results at some nonprofits and others not so much. The difference is how staff members bridge a few common gaps as AI use becomes more intentional, governed, and transparent.
Data from a new report from the Blackbaud Institute, “Bridging the Effectiveness Gap,” shows just a small number of organizations have moved past experimentation with AI (roughly 10%) whereas most organizations (75%) in the social sector are using AI in fragmented, individual ways — achieving only limited organizational impact, and missing the more transformational shifts the technology enables. The other roughly 15% have not adopted or approved the use of AI.
It’s AI-Adaptive versus AI-Emerging. And, there are gaps in the implementation — Data-Readiness Gap and a The Transparency Gap, according to report authors.
In the described Data-Readiness Gap, fewer than 20% of respondents would rate their organization’s data health as excellent, compared to 38% at AI-Adaptive organizations. “Data readiness is the foundation of AI readiness. Respondents at AI-Adaptive organizations express significantly greater confidence in their data’s accuracy, validity, timeliness, completeness, consistency, and uniqueness,” the authors wrote. AI for data cleaning is an unrealized opportunity for AI- Emerging organizations.
The Transparency Gap is when donors expect clarity about AI use, but disclosure is not yet the standard practice. Of those polled, 76% of donors say it’s important for organizations to clearly disclose when and how AI is used, yet only 26% of professionals say their organization does this today. This creates a widening mismatch between donor expectations and current organizational norms.
At the same time, data in the report shows that organizations where gaps are addressed, treating AI not as a tool but as a governed framework for transformative growth are seeing substantial benefits across revenue, donor retention, and staff productivity.
The data was derived via two parallel surveys conducted in March 2026 in the United States, in partnership between the Blackbaud Institute and Edge Research. Responses were received from 1,389 social impact professionals and 1,034 donors who support social impact organizations (defined as nonprofits, healthcare organizations, K–12 schools, higher education institutions, and foundations).
According to respondents, 34% of those reporting to be AI-Adaptive exceeded revenue goals whereas 17% of those not using AI exceeding revenue goals. There were multiple levels of revenue again in organizations where staff are “aware,” “active” and “operational.”
When asked about freeing up time and operating more efficiently, it was 81% positive on both counts for AI-Adaptive Organizations versus 18% and 16% respectively for organizations where AI was not in use. Respondents answered 16 questions regarding AI use.
There are safeguards on use even at AI-Adaptive organizations with 60% responding human review or oversight is required with AI-generated outputs before they are used.
While the IT department unsurprisingly pushes for AI (34%), executive leadership is not far behind and 30% with fundraising staff also registering 30%.
You can see all of the data in the 27-page report by clicking here.
