Nonprofit
Author: Unit4 Communications November 18, 2025 4 min read

AI readiness for nonprofits: A blueprint for transformation

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In a recent webinar hosted by Unit4, Chris Brewer, Growth Director, Nonprofit, was joined by Corey Bakhtiary, VP of Strategy and Innovation at Argano, to explore how AI is reshaping nonprofit operations. 

The discussion centered on the challenges, opportunities, and best practices for AI adoption, with a focus on organizational, technical, and cultural readiness.

Amid rising demands, budget constraints, and increased stakeholder expectations, nonprofits are under pressure to leverage technology strategically. 

This blog distills insights from that conversation to help nonprofits assess their AI readiness, avoid common pitfalls, and create a roadmap for responsible and effective adoption.

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The nonprofit AI landscape

Nonprofits face a unique challenge: 

  • 98% of sponsors are urging CFOs to prioritize AI, yet 64% of those CFOs are hesitant, unsure where to start. 

  • 84% lack specific guidance on which AI tools to adopt. 

This disconnect highlights the gap between the expectation to innovate and the practical knowledge required to do so.

AI’s promise for nonprofits is not to replace staff but to amplify human capacity. Teams can leverage AI to automate repetitive tasks, accelerate decision-making, and optimize resource allocation, helping organizations deliver greater impact with limited resources.

Why AI matters

The webinar emphasized several critical benefits of AI for nonprofit organizations:

  • Efficiency gains: Automating repetitive work such as donor outreach, case updates, and reporting frees staff to focus on high-value, human-centered activities.
  • Improved decision-making: AI can analyze vast datasets to identify patterns in donor behavior, program outcomes, and community needs, enabling leaders to make informed, data-driven decisions.
  • Enhanced program delivery: AI helps match volunteers to opportunities and tailor services to specific community needs, increasing program effectiveness.
  • Transparency and trust: Tracking the correlation between donor funds, program activities, and outcomes builds accountability and strengthens stakeholder confidence.
  • Optimized resource allocation: Predictive AI can forecast staffing needs and guide resource deployment to initiatives with the highest measurable impact.

As Corey noted, AI’s role is to create capacity, enabling nonprofits to serve more people more efficiently without compromising their mission or values.

 

 

Demystifying AI terminology

During the webinar, Corey clarified key concepts that often cause confusion:

  • Agents: AI “workers” that perform specific actions, such as pulling data, answering questions, or escalating decisions for human review.

  • Co-pilots: Assistants that augment human work; they support rather than replace staff.

  • Data readiness: Clean, unified, and connected data is crucial; garbage in, garbage out.

  • Orchestration: The connective tissue linking multiple AI tools, providing a single entry point for efficient, context-aware reasoning.

Understanding these terms is a foundational step in preparing an organization for AI adoption.

The four-step blueprint for AI readiness

The discussion highlighted a structured, phased approach to AI readiness:

1. Inform: Building foundational knowledge

  • Objective: Educate staff and stakeholders about AI and its practical applications.
  • Activities: Conduct briefings, workshops, and establish a shared data language to remove misconceptions and build a common understanding.

2. Assess: Identifying opportunities and readiness

  • Objective: Evaluate organizational readiness and identify high-value AI use cases.
  • Activities: Host workshops to ideate applications aligned with your mission. Assess data quality, technical infrastructure, and internal skill gaps. Identify “shadow AI”, unauthorized tools employees may already be using.

3. Transform: Piloting and building momentum

  • Objective: Demonstrate AI’s value through targeted pilot projects and develop internal champions.
  • Activities: Start with small, high-impact pilots to showcase benefits and build trust. Focus on quick wins to maintain momentum, knowing that over 90% of AI pilots fail to scale without careful planning.

4. Perform: Scaling and continuous improvement

  • Objective: Deploy AI solutions organization-wide and establish processes for ongoing management.
  • Activities: Scale successful pilots, monitor for issues like “data drift,” and iterate to identify subsequent high-value use cases. This cyclical approach ensures continuous improvement and broader organizational adoption.

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Common adoption challenges

Two recurring obstacles surfaced during the webinar:

  • Post-assessment paralysis: Organizations may need foundational work, like Cloud migration or data cleansing, before AI can be deployed effectively.

  • Pilot-to-scale gap: Successful pilots often fail to scale due to redundant efforts, lack of strategic planning, or insufficient buy-in from leadership.

Addressing these challenges early is essential to preventing stalled AI initiatives.

Real-world AI applications

Several examples were highlighted during the webinar:

  • Donor outreach automation: Freeing staff to focus on relationship-building rather than repetitive communications.

  • Financial and vendor oversight: AI bots identified anomalies in vendor data, providing alerts without making autonomous decisions, supporting compliance and risk management.

  • Program optimization: AI models can match volunteers to the right projects or predict where interventions will have the greatest impact, increasing program effectiveness.

These examples demonstrate how AI can augment existing capabilities rather than replace human expertise.

Technology as a strategic enabler

The discussion reinforced that AI is most effective when paired with strong infrastructure and data foundations:

  • AI-ready platforms: Secure, integrated systems enable seamless adoption of AI tools.

  • Strong data layer: Centralized, clean, and connected data ensures AI outputs are reliable and actionable.

  • Expert partners: Collaborating with vendors who understand nonprofit operations accelerates adoption and maximizes ROI.

By aligning technology with mission-critical outcomes, nonprofits can transform operational efficiency while enhancing program delivery.

Next steps for nonprofit leaders

Chris and Corey recommended a pragmatic approach:

  • Start small: Focus on high-impact, low-effort pilots.

  • Educate and engage: Build internal understanding and trust in AI capabilities.

  • Partner strategically: Work with vendors who understand the nonprofit sector.

  • Invest in infrastructure: Ensure AI-ready platforms and strong data management practices are in place.

AI readiness is not a one-time project; it’s a strategic journey that requires continuous learning, iterative adoption, and an emphasis on human-centered outcomes.

Ready to explore AI for your nonprofit?

Nonprofits looking to accelerate AI adoption can start by conducting a readiness assessment, piloting select initiatives and partnering with experts who understand the sector. 

Platforms with integrated AI capabilities, strong data foundations, and secure architecture can enable organizations to unlock efficiency, enhance program delivery, and amplify impact.

Watch the full on-demand webinar to hear the complete discussion between Chris Brewer and Corey Bakhtiary, including practical examples and actionable guidance for nonprofits looking to adopt AI responsibly.

You can also watch a demo or talk to the Unit4 sales team today. Our experts will help you build a tailored roadmap for AI adoption.

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