AI & Nonprofits

Market Summary 2025

beneAI | November 2025

Download the PDF report here.

A Sector at a Crossroads

The nonprofit sector has arrived at a critical inflection point, defined by the collision of two powerful and opposing forces: a debilitating internal operational crisis, driven by unprecedented staffing shortages and a persistent reliance on manual processes; and a transformative external technological revolution, led by rapid, democratized access to artificial intelligence.

Aggregate findings from five key 2025 market research reports on the state of nonprofits and technology paint a clear picture of this. The organizations that invest in building new digital capabilities today will be the ones that will likely see the greatest efficacy tomorrow. Those that fail to update skills, identify drag, or treat AI as a superficial add-on or passing fad will fall behind, face declining revenue, see a widening productivity gap, and face obsolescence.

Key Themes

Operational Crisis

Staffing has emerged as the #1 challenge for the sector (58%), surpassing concerns about funding (55%). This is compounded by deep-rooted inefficiencies, with 41% to 49% of nonprofits citing a lack of process automation and 35-44% burdened by manual, time-consuming reporting.

Data Deficit

Data-driven decision-making is elusive. While 85% of nonprofit leaders recognize the importance of metrics, only 9% consider their organizations highly data-driven.

Governance Vacuum

The gap between high adoption and low oversight represents a significant and alarming sector-wide vulnerability. Only 14% of have a formal AI policy in place.

Return on Investment

Despite these challenges, the business case for strategic technology is known. 72% of nonprofits using AI have met or exceeded their fundraising targets in the last year, with a clear link between higher levels of technology integration and fundraising revenue growth.

The AI Paradox

Interest in AI is nearly universal, with 85% of nonprofits exploring its use and 74% actively using AI. However, this adoption is reactive, not strategic: only 24% have a formal AI strategy.

Widespread Adoption, Anemic Planning.

The AI Strategy Gap. There is a chasm between AI interest and proactive planning. The 'State of AI in Nonprofits’ report from TechSoup and Tapp Network identifies this as a primary strategic gap. While 85.6% of nonprofit professionals are actively exploring AI tools like generative AI and predictive analytics, a staggering 76% of their organizations do not have a formal AI strategy in place. This leaves only 24% with a documented, actionable plan. This gap is not a passive planning failure; it is an active missed opportunity. Nonprofits that delay adoption and strategy risk decreased productivity and a larger-than-expected learning gap, putting them at a significant disadvantage.

High Adoption, Low Governance. The strategic gap becomes even more concerning when contrasted with adoption rates. While only 24% have a plan, the Blackbaud report finds that 82% of nonprofits are already using AI tools. This discrepancy (a 58-point gap between usage and strategy) suggests that a majority of the sector is engaging in "shadow AI." This is a reactive, staff-led adoption of tools without formal organizational oversight, strategy, or governance. Primary use cases confirm this: 33% are using AI for content marketing and 24% for grant writing, with free, generative platforms for content creation as the most common application. This widespread, ungoverned adoption is illustrated by another finding: only 14% of nonprofits have a formal AI policy. This means the vast majority of organizations using AI are doing so without guidelines, exposing them to significant unmitigated risks related to data privacy, ethical blind spots, and bias.

Resource Disparity Barrier. This strategy gap is not uniform; it is, in large part, a capacity and resource gap. AI adoption is bifurcating the sector. Nonprofits with annual budgets exceeding $1 million are adopting AI tools at nearly twice the rate of their smaller counterparts. This disparity is explained by a critical lack of internal capacity. 43% of nonprofits rely on just one or two staff members to manage all IT and AI-related decision-making. This thin capacity creates a high barrier to effective implementation, leaving smaller organizations further behind.

Headwinds

The sector's AI strategy gap is a symptom of more profound and persistent operational headwinds, primarily a crippling staffing crisis and a deep-rooted lack of internal efficiency.

  • The AI strategy gap is not a failure of imagination. It is a symptom of a deeper, more fundamental crisis: a lack of operational capacity. This is a moment of reckoning for the sector. For the first time, staffing (58%) has made a dramatic shift to become the top external challenge facing nonprofits, overtaking competition for funding (55%) and economic uncertainty (49%). This staffing crisis is amplified by a crippling level of internal inefficiency. The top internal operational challenges, which have remained stubbornly persistent for years, are:

    • Lack of process automation and organizational efficiency (41-49%).

    • Reliance on manual, time-consuming reporting (35-44%).

    • Lack of real-time visibility into key metrics and performance (34-44%).

    • Inefficiencies and delays due to multiple, disparate systems (29%).

  • These data points reveal a vicious cycle of "digital poverty" that effectively neutralizes AI ambitions. Nonprofits are trapped: they are experiencing a staffing crisis 4 and are simultaneously buried in manual, non-automated work. As noted, 43% have only one or two people responsible for IT and AI. This combination means the very staff members who would theoretically be tasked with developing a future-facing AI strategy are instead fully consumed by the present-day, manual tasks of patching together disparate systems and generating reports by hand. Organizations cannot adopt capacity-building technology (AI) because they lack the foundational capacity (staff time, automated processes) to even evaluate and implement it.

  • This operational drag has a direct, negative impact on data-driven decision-making. There is a large gap between aspiration and reality: 85% of leaders recognize metrics are important, but only 9% of nonprofits consider themselves highly data-driven; 34% collect data but are not fully leveraging that data. This inability to leverage descriptive data explains why some advanced AI applications remain out of reach. Only 12% of nonprofits are leveraging predictive analytics. The sector cannot move to predictive data use when it is still struggling to escape manual, non-real-time descriptive data collection and reporting.

Potential ROI

Despite the operational headwinds, the return on investment for improving digital maturity is promising, offering a direct path to financial sustainability, productivity gains, and better outcomes:

  • For organizations that can break the cycle of operational drag, the rewards are clear, immediate, and financial. Organizations with higher levels of technology integration across all processes, including fundraising, service delivery, and internal operations, are more likely to report revenue growth and less likely to report revenue decline. This is a strategic lever in a difficult economic climate where 43% of nonprofits face decreased funding and 40% see increased demand for services. The 72% of nonprofits that successfully met or exceeded their fundraising targets last year are more likely to be those with higher digital maturity. The strategic priority for nonprofit leaders in 2025 is financial sustainability, and digital maturity is directly linked to this goal. The top blocker to digital maturity is reliance on manual processes. Therefore, a direct path to achieving the sector's top priority of financial sustainability would be to invest in solving its top internal challenge of process improvement and automation.

  • While 99% of nonprofit professionals agree AI has a meaningful place in their organization, most struggle with how to use it effectively. Only 31% are collaborating strategically with AI, viewing it as a creative partner or expert advisor rather than a simple tool. These AI strategists report that it helps them to be 29% more productive. The majority of organizations without formal AI strategies are not just facing abstract risks, they are actively forfeiting verifiable productivity gains. This strategy gap is, in a way, a productivity gap.

  • The ultimate return on technology adoption should be the direct amplification of mission impact. This is not a future-state goal; it is already happening. AI-powered nonprofits are already transforming millions of lives and demonstrating a clear model for scaling social impact. This enhanced technological capacity allows organizations to move beyond simple automation to make smarter, data-driven decisions and gain the ability to automate tracking and reporting of outcome metrics. This allows technology to free up human capacity to focus on the core mission, turning the productivity gains directly into better, and more scalable, outcomes.

Starting Points

For organizations ready to begin, the 2025 surveys show a clear consensus on two high-impact, accessible starting points:

Fundraising and Grant Writing: 60% show strong interest in AI for this area. 25% are already using AI for grant writing, with “prospecting" and "wealth screening" as other emerging use cases.

Marketing and Operations: 33% are using AI for content marketing, which is a primary use case for "AI-Assisted" organizations in 2025.

Read the full report for more.

Bibliography

Atlassian. (2025). The nonprofit AI collaboration index 2025.

Blackbaud Institute. (2025). The status of fundraising 2025.

Fast Forward, & Google.org. (2025). 2025 AI for humanity report.

Sage. (2025). 2025 nonprofit technology impact report.

TechSoup, & Tapp Network. (2025). The state of AI in nonprofits: 2025 report.