As artificial intelligence (AI) becomes more embedded across the social sector, nonprofit organizations are advancing along an AI maturity journey. Many have moved beyond initial experimentation and are beginning to realize value through targeted use cases that improve productivity and support mission-driven work. The question facing leaders is no longer whether to use AI, but what capabilities must be developed next to maximize its long-term impact.

For most organizations, the journey towards optimization will usher them through similar phases: experimentation, adoption and workflow integration, and ultimately organizational transformation. Early efforts often focus on testing tools and building familiarity. As usage expands, attention shifts to applying AI in specific functions and workflows. The greatest opportunities, however, emerge when organizations begin redesigning how work moves across teams, how decisions are made, and how services are delivered.

Understanding where the organization sits on this maturity path can help leaders make more intentional decisions about strategy, governance, workforce readiness and investment priorities. The following five leadership priorities are designed to help nonprofit leaders move beyond isolated AI initiatives and build the capabilities needed for sustainable, mission-aligned transformation.

AI maturity journey

Experimentation - Testing AI tools and building familiarity

Adoption - Intergrating AI into individual productivity, workflows and enterprise processes

Organizational transformation - Rethinking operating models, service delivery and mission execution

1. Strengthen data security mindset

As nonprofits adopt AI, protecting their donor’s sensitive data becomes even more critical. AI’s reliance on large datasets can increase exposure to privacy, security and compliance risks, particularly when tools are integrated across multiple systems and workflows.

Given that more than 80% of nonprofits are already using AI in some form, even organizations with strong data practices should reassess how data flows through AI-enabled processes.1 This includes evaluating how information is stored, accessed and used by third-party tools.

light bulbLeadership consideration: Focus and trust

AI introduces new dimensions of risk that extend beyond traditional data protection, elevating the importance of governance and stakeholder trust.

Leadership teams should consider:

  • The level of visibility and oversight required for how AI tools use and process organizational data
  • Whether existing data policies adequately address AI-specific risks, including model behavior and third-party exposure
  • How the use of AI, particularly in donor or beneficiary contexts, may be perceived by stakeholders

2. Develop a mission-aligned AI strategy

Some organizations are piloting AI tools without a cohesive plan, often in a rush to avoid falling behind perceived technological shifts. This can lead to fragmented adoption, duplicated efforts and staff uncertainty. A clear AI strategy should identify where the technology can most meaningfully advance mission delivery, whether through donor analytics, program evaluation, volunteer coordination or communications.

Focusing on a small number of targeted, high-value applications helps assure AI enhances organizational effectiveness rather than becomes an ad-hoc addition or creates new forms of technical debt.

light bulbLeadership consideration: Defining value and measuring ROI

As nonprofits move beyond early experimentation, the key question shifts from “where can we use AI?” to “where does AI create meaningful value?”

Early adopters are already seeing measurable results, including 20% to 30% increases in donations through more personalized, AI-supported outreach.2 This underscores the importance of defining success clearly and prioritizing use cases that drive meaningful outcomes, not just incremental efficiencies.

Leadership teams should evaluate AI through a broader definition of value, including:

  • Improved donor acquisition, retention or engagement
  • Enhanced decision making through better data and insights
  • Expanded program reach or more effective resource allocation
  • Increased staff capacity to focus on relationship-driven and mission critical work

3. Establish an internal AI governance framework

An AI governance framework provides the structure needed for responsible, ethical and mission-aligned adoption. As organizations begin to scale usage across functions, informal or inconsistent practices can create risk, inefficiency and uncertainty. A defined governance framework helps affirm that AI use is intentional, coordinated and aligned with organizational values.

This is especially important given the growing gap between adoption and oversight. Only an estimated 10% to 24% of nonprofits have formal AI governance policies or frameworks in place, highlighting how quickly usage is outpacing structured oversight.3

light bulbLeadership consideration: Decision rights and accountability

As AI becomes more integrated into day-to-day operations, one of the most important questions is “who owns the decisions?”

Leadership teams should consider:

  • Where human oversight is required versus where decision making can be augmented by AI tools
  • How accountability is maintained when AI influences outputs, recommendations or interactions
  • How governance structures will evolve as AI use expands beyond initial pilots

4. Build staff confidence through training and guidance

Nonprofit staff are consistently reporting uncertainty when it comes to using AI, highlighting a clear gap between access to tools and the ability to use them effectively.4 Without deliberate support, this can lead to inconsistent adoption, underutilization or misuse across teams.

Organizations should provide role-specific training that builds foundational understanding and supports practical application, including guidance on common use cases and clear expectations for appropriate use, commonly referred to as the “Shadow AI” dilemma. One of the greatest AI governance risks is no longer whether employees use AI, but whether they use AI outside the organization’s approved environment.

light bulbLeadership consideration: Workforce transformation

AI adoption is not just a technology shift, but a workforce transformation that will reshape how work gets done across the organization. Despite growing usage, more than 90% of nonprofit professionals report feeling unprepared to fully leverage AI, and many organizations lack formally trained staff.5

Leadership teams should consider:

  • How job responsibilities and expectations may evolve, particularly for functions like fundraising, communications and operations
  • The level of AI literacy required across the organization, not just within technical teams
  • How to address uneven adoption, where some teams or individuals move quickly while others lag behind

5. Prioritize high-impact, low-risk use cases for early wins

Nonprofits often see the greatest initial value from practical AI applications that reduce administrative burden and improve efficiency. These shifts are already delivering measurable efficiency gains, with AI saving nonprofits an estimated 15 to 20 hours per week in administrative time.6 Common early use cases include drafting donor communications, supporting grant writing, streamlining reporting and assisting with internal workflows. These applications can help organizations quickly build familiarity with AI while delivering tangible time savings.

At the same time, thoughtful prioritization is critical. Focusing on use cases that are both impactful and low risk allows organizations to build momentum without introducing unnecessary complexity or exposure. Early wins can also help demonstrate value to leadership and staff, creating a foundation for more advanced adoption over time.

light bulbLeadership consideration: Workflow and operating model evolution

As AI capabilities advance, the opportunity extends beyond isolated tasks toward rethinking entire workflows and how work is structured across the organization.

Leadership teams should consider:

  • How emerging tools, including AI-driven agents, may coordinate multiple steps within a workflow with limited human intervention
  • Which activities should remain human-led, particularly those involving relationship management, stewardship and trust building
  • How increased automation may reshape capacity planning, staffing models and the allocation of resources over time

From insight to action

Nonprofits are entering a new phase of AI adoption, shifting from experimentation to more deliberate decisions around strategy, governance, workforce and long-term impact. Organizations that approach AI thoughtfully will be better positioned to scale their mission while maintaining trust.

Rather than viewing AI solely as an efficiency tool, leaders should treat it as an operating capability that shapes how work gets done. Aligning AI with mission priorities, establishing governance and investing in staff readiness will be critical to realizing its full potential.

Key actions for nonprofit leaders

  • Identify two to three priority use cases where AI can meaningfully support mission delivery or revenue growth.
  • Define how success will be measured, including both efficiency gains and mission-related outcomes.
  • Establish clear ownership and governance for AI-related decisions across teams.
  • Review and update data policies to address AI-specific risks and use cases.
  • Invest in staff training to build baseline AI literacy and support consistent adoption.

Nonprofit Strategy & Solutions Group

PNC’s Nonprofit Strategy & Solutions Group serves as a dedicated partner committed to empowering nonprofit organizations to achieve their missions. By combining national expertise with local knowledge, we provide comprehensive education and advice on governance, philanthropy and financial sustainability — going beyond asset management to deliver actionable insights that address the most pressing challenges nonprofits face. With our deep community ties, practical nonprofit leadership experience and strong local market presence, we provide meaningful solutions that optimize resources and deliver a sustainable impact.

For more information, contact the team at IAMNonprofitStrategy@pnc.com.