Three key takeaways from our conversation with non-profit CEOs who are actively piloting, adopting, and implementing AI technology.
Culture is the largest blocker to AI transformation, with stakeholder buy-in being critical to success. |
Comprehensive upskilling and ethical AI training are essential for future-proofing organizations. |
AI adoption requires breaking down silos and shifting from "me" to "we" mindsets across leadership. |
CEO attendee
RRA AI CEO Labs
01. For efficiency and operational improvement. CEOs discussed how AI is helping streamline mundane or routine tasks across their organizations, from administrative work to customer service interactions. Most leaders had either deployed AI copilot tools or personally experimented with the technology for taking minutes, writing, or integrating GenAI into educational curriculums.
02. To address unique sector challenges. The conversation highlighted how AI offers specialized solutions for non-profit challenges. In environmental conservation, one CEO shared how AI's image processing capabilities were reducing human-animal conflict by warning nearby communities of animal presence. However, disaster relief organizations expressed concerns about AI potentially reducing the human touch in relief efforts. Leaders emphasized the need for balance—using AI to improve operations while maintaining the compassionate human connections that are central to their missions.
03. To enhance data utilization. Participants recognized that effective AI implementation requires a strategic approach to data management. One CEO advised creating a centralized data store accessible across the organization, describing data as "the lifeblood of the modern enterprise." The group discussed the importance of keeping data from individual silos until as close to the point of constituent interaction as possible, enabling more personalized and effective service delivery while maintaining appropriate privacy standards.
Our attendees shared the opportunities, challenges, and lessons they had faced when implementing AI across their organizations.
Cultural resistance was seen as one of the largest blockers to transformation. One CEO stated: "Our issue will be stakeholder buy-in. Getting the leadership team to sync will be easier, but we've got people in the organization who want AI transformation and education to be done right now in a systematic way, but then we have folks saying regularly that AI is the end of the world."
The discussion emphasized that cultural change starts at the top. "Leaders should be at the forefront of the buy-in; if leaders don't use the AI tools themselves, they will drive a gap," shared one CEO. Several participants highlighted the value of identifying and rallying around AI "superusers" within the organization to demonstrate practical applications and benefits, helping to address skepticism and fear.
Non-profit leaders face unique cultural challenges, as many of their employees are deeply mission-driven and may be concerned about AI changing the nature of their work. The group discussed the importance of framing AI as an enhancement to their mission rather than a replacement for human connection.
There was consensus that all employees needed the tools and skills to utilize AI—for innovation to flourish and to create versatility in the workforce, but with a strong caveat on ethical use. The group discussed how targeted education and training initiatives will support creating a workforce that is agile, informed, and capable of navigating the complexities of AI-driven business landscapes. Several CEOs shared how they were implementing AI literacy programs across all levels of their organizations, recognizing that different roles would require different depths of understanding.
Participants also addressed the ethical dimensions of AI upskilling. For non-profits working in sensitive areas like disaster relief, healthcare, or vulnerable populations, ensuring that staff understood both the capabilities and limitations of AI was considered essential. Several CEOs emphasized that training must cover not just how to use AI tools, but when not to use them—preserving human judgment in critical decisions affecting those they serve.
There was agreement that AI was an "everyone problem," requiring collaborative, cross-functional approaches to succeed. As one CEO expressed: "We needed everyone to have a more enterprise level mindset. It's not a triangulation of 'up to the CEO and back,' it's about working together, breaking down silos, breaking the me into we."
The conversation also touched on the transformation of leadership roles and the necessity of building trust and connectivity within the executive team to facilitate meaningful change. Leaders need to pay constant attention to the experiences of their teams as they interact with AI in their roles, and accept that although productivity may increase, employees may feel additional cognitive burdens.
Board engagement was identified as crucial to AI strategy. The group agreed that AI transformation was absolutely a board-level issue, and if it was not represented in the boardroom, "it's most of the time not getting done in the organization."
Some organizations were addressing board engagement through alternative structures, such as creating AI/Tech advisory boards. This approach offered benefits of both speed—with board replacements and searches taking more time and planning—and the ability to incorporate broader expertise specific to AI implementation in the non-profit context.