The Growing AI Gap Between Social Sector Organizations 

In general, social sector organizations seem to be cautiously optimistic that artificial intelligence (AI) has the potential to increase workplace capacity and improve fundraising efforts, service delivery, and impact measurement. Organizations are already using AI tools to streamline communications, increase outreach, and support grant writing, with some organizations reporting a savings of 15-20 hours weekly on administrative tasks.   

However, despite this enthusiasm around AI, social sector organizations continue to trail their for-profit counterparts in adopting these tools, and a widening gap within the sector itself is similarly stark. Nonprofits with annual revenues over $1 million are embracing AI at nearly twice the rate of smaller organizations. Considering over half of all nonprofit organizations bring in less than $1 million, a substantial segment of the sector at a competitive disadvantage. 

This gap threatens to undermine the collective mission of the social sector. If left unaddressed, it could deepen existing inequities, limit community responsiveness, and create a two-speed system in which only some organizations can fully harness emerging technologies. 

• Financial constraints: AI integration can have steep barriers to entry, including costs for software licenses, system integration, and ongoing subscription or compute fees. Even when initial tools are affordable, long-term costs for customization, enhancement, and compliance-driven auditing can place AI out of reach. As The Bridgespan Group points out, the overall lack of funding is compounded by a nonprofit financing model that often treats technology as a luxury, rather than an integral strategic investment. 
• Lack of specialized talent: Advanced AI tools often require specialized skills, such as machine learning engineering, systems integration, data science, cybersecurity, and API management. Organizations with revenues under $1 million rarely maintain such roles. In fact, roughly 41% of nonprofit organizations rely on just one staff member to make all AI decisions. This can lead to bottlenecks and makes it difficult to establish formal data governance, including AI governance committees, policies, and quality controls. 
• Limited technology and data infrastructure: Legacy systems, inconsistent data practices, or outdated hardware can also make it difficult to implement AI solutions. Even well-resourced nonprofits and for-profit companies struggle with limited AI capacity within existing enterprise systems, while organizations with basic or homegrown enterprise systems may not even have the option to purchase plug-and-play AI add-ons. Additionally, organizations serving smaller communities typically do not generate or store the large datasets required to train or fine-tune models.  

The disparities arising in practice include: 

• Gaps in mission effectiveness: AI can increase efficiency, expand hours of availability through automated tools, enhance case management, and streamline reporting. 
• Widening funding disparities: Funders increasingly expect strong data practices, predictive analytics, and evidence of measurable outcomes. Harnessing predictive analytics can substantially boost fundraising efforts, with organizations seeing donor response increases of 20% to 30%. 
• Reduced responsiveness to local needs: As well-equipped organizations scale capacity with AI, local and grassroots groups, which are often those closest to community realities, risk falling behind.  

Ultimately, the social sector, technology sector, and philanthropic community must collaborate to ensure that technological progress strengthens, rather than fragments, our collective impact. 

Overall, nonprofits of all sizes are optimistic about the impact of AI and report an eagerness to experiment with AI solutions. By investing in shared resources, targeted capacity building, and policies that promote transparency and accessibility, we can ensure that all social sector organizations are able to integrate human-first AI solutions effectively. With thoughtful action, the sector can harness AI not as a force for inequality but as a tool for expanding opportunity, strengthening communities, and advancing a more equitable future. 

• NTEN’s Equity Guide for Nonprofit Technology is a practical tool for promoting equitable use and implementation of technology within social sector organizations to address systemic inequities. NTEN provides resources, training, and community support to help nonprofits use technology strategically and equitably. 
• TechTonic Justice has a new Decision Guide for Considering AI Use that offers a helpful set of questions as organizations gauge their AI readiness.  
• TechSoup’s 2025 State of AI in Nonprofits Report shares how nonprofits are using AI, the common challenges they face, and how they determine their AI readiness. 
• For even more frameworks and templates to put into practice, see Social Current’s Knowledge and Insights Center topic spotlight on Opportunities and Risks for Implementing AI in Human Services.