AI ADOPTION

IN NONPROFITS

Challenges and Opportunities

Unlocking the potential of AI for 46,000+ nonprofits in NYC to revolutionize education and workforce development.

A Research Report by Decoded Futures at the Tech:NYC Foundation

In Short…

What We Did

  • Polled 80+ employees from 50 education and workforce nonprofits, tech companies, and other Tech for Good intermediaries

  • Conducted interviews with 25 organizations

  • Ran 3 pilot programs based on the interviews

What We Recommend

We’ve identified actionable recommendations for nonprofits to assist in integrating AI into their workflow.

We also provide insights into what companies, philanthropists, funders, and other stakeholders can do to better support nonprofits as they explore transformative, AI-powered solutions for social services in the nation’s largest city.

What We Found

Nonprofits face a number of challenges when incorporating AI into their workflow, including resource constraints, lack of clear starting points, and difficulty accessing relevant training and support.

At Decoded Futures, we empower nonprofits to unlock the transformative potential of AI. By connecting nonprofits with technologists, resources, AI upskilling, and introductions, we aim to create innovative, responsible solutions that address critical challenges in the social sector.

We sought to understand nonprofits’ current needs and aspirations for AI, as well as tech companies’ activities toward fulfilling them.

We hope this report will empower nonprofits, funders, and Tech for Good intermediaries to better prepare for and build toward innovative AI solutions.

Our Goal

AI adoption in NYC’s education and workforce nonprofits reflects a diverse spectrum. Some organizations are experimenting with AI for curriculum design or operational tasks, while others remain in exploratory phases. Key takeaways include:

  • Experimentation is common, but strategic adoption is rare: While nonprofits are intrigued by AI, lack of resources and training slows progress.

  • Competing priorities create paralysis: Leadership often hesitates or stalls on policy creation vs. experimentation, as the industry grapples between AI’s promises and its ethical concerns.

  • Insufficient AI support: Many tech companies offer support to nonprofits on technology. However, nonprofits struggle to find this support and the help offered is often not right-sized to their needs.

Despite these challenges, the appetite and interest for AI adoption is strong. With proper guidance, nonprofits can leverage this moment to enhance their impact.

The State of AI in NYC Nonprofits

AI Maturity Scale

The Decoded Futures team uses an AI Maturity Scale to quickly understand where nonprofits stand in their AI adoption journey. It categorizes organizations into three key stages, offering insights into their current capabilities and opportunities for growth:

  • Just beginning to explore AI, but may have limited awareness, lack leadership buy-in, or feel overwhelmed by getting started. These nonprofits tend tofocus on building foundational knowledge and identifying low-risk, high-impact pilot projects.

  • Early experimenting with AI, often driven by passionate internal champions or leadership support, but AI is not yet integrated into their core operations. These nonprofits prioritize scaling successful experiments and aligning AI initiatives with broader organizational goals.

  • Active utilization of AI as a strategic tool across their programs and operations. These organizations have developed fluency in AI, implemented policies, and established some internal expertise. They are leaders in their peer group, but often still need support on implementation and scale. 

As AI continues its rapid evolution, nonprofits find themselves at a critical juncture. The potential of AI to transform education and workforce development has never been greater — unlocking efficiencies, scaling personalized learning, and enabling data-driven insights.

Yet, this moment of opportunity is shadowed by profound challenges. Nonprofits grapple with fundamental questions: How can AI be used responsibly to enhance their missions without compromising equity and trust? What does adopting this technology mean for their staff, programs, and the communities they serve?

Amidst this uncertainty, organizations are inundated with competing messages. One narrative emphasizes AI as a transformative force, heralding urgency with the risk of being left behind. The other warns of the inherent risks—data bias, inequity, and misuse—that can accompany rapid adoption. Together, these "two voices" encapsulate the dilemma that leaves many nonprofits hesitant, if not paralyzed, at the threshold of AI integration.

The Crossroads of Opportunity and Caution

Adopting AI can seem daunting for nonprofits, but starting with a clear, manageable approach can pave the way for meaningful integration. By focusing on small, practical steps and fostering a culture of learning, nonprofits can build momentum while minimizing risks.

A collaborative effort that includes internal champions and external partners ensures the organization has the support needed to navigate challenges effectively. At every step, ethical considerations — like data privacy and equity — must remain central to ensure that AI enhances rather than detracts from the mission.

Here are five actionable best practices for nonprofits:

  1. AI policy can be ‘good enough’: Formal policies may not be essential for getting started, so long as organizations focus on smaller, low-risk, practical AI experiments to build familiarity and confidence.

  2. Start small: Pilot manageable projects that address immediate needs and allow for quick learning cycles.

  3. Just hit ‘publish’: The latest wave of AI allows organizations to embrace a mindset of continuous learning, testing ideas, and adapting based on results. 

  4. Partnerships are key: As AI is still an evolving field, technologists and nonprofits need to work together to navigate implementation and best practices.

  5. Establish a culture of continuous learning: Nonprofits with the highest adoption rates of AI tend to be ones who put a prize on regular, continuous use of AI tools.

These steps lay a strong foundation for nonprofits to responsibly embrace AI and unlock its transformative potential.

Best Practices for AI Adoption

Bridging the Gap: Recommendations

2. Building Collaborative Infrastructure

Establish centralized resources to simplify nonprofits’ access to AI tools, training, and best practices. This could include a “one-stop shop” hub offering curated information on AI solutions, case studies, and peer success stories. By creating a collaborative ecosystem, funders and technologists can lower barriers to adoption and ensure nonprofits have the guidance needed to deploy AI responsibly and efficiently.

1. Hands-On Training for Impact

Equip nonprofits with accessible, hands-on AI training designed to address real-world challenges. Programs should focus on active learning with technologists and nonprofits working together. Funders then need to provide ongoing support to ensure organizations can move beyond basic familiarity to meaningful integration. This approach helps nonprofits build the skills and confidence needed to leverage AI effectively while navigating its complexities.

3. Encouraging Cross-Sector Experimentation

Strengthen partnerships between funders, technologists, and nonprofits to align resources and expertise for innovation.  Much of the social sector’s work is not just training but identifying how AI can uniquely support nonprofits, and that requires nonprofits, technologists, and funders working together to experiment, explore, and learn about what works and what doesn’t.