As an organization focused on environmental sustainability and systems change, The Regenerative Agriculture Foundation (RAF) was curious about AI’s ability to boost productivity and impact. Though team members had begun experimenting with AI tools in their work, the staff had significant concerns about the technology’s broader implications.
In addition to asking difficult questions about AI’s environmental impact, including energy consumption, water usage, and greenhouse gas emissions, RAF was concerned about data privacy, intellectual property, surveillance, consent, and the ethical implications of adopting rapidly evolving technologies.
RAF engaged Software for Good and a partner agency, Soil and Shadow, to help deepen their understanding of the AI landscape, evaluate opportunities and risks, and develop an approach to AI use that aligns with their values.
As part of the two-day workshop, Software for Good facilitated a full day of learning focused on AI literacy, ethical technology adoption, and organizational decision-making. The workshop created space for RAF participants to explore the intersection of AI, organizational values, environmental responsibility, and operational goals.
Through facilitated discussion, collaborative exercises, and evaluation of different frameworks, the RAF team deepened their understanding of:
- The current AI landscape and emerging tools
- Environmental considerations related to AI technologies
- Data privacy, intellectual property, and governance concerns
- Potential opportunities and risks for the Foundation
- Organizational approaches for evaluating and adopting AI responsibly
The engagement helped move the conversation from broad curiosity and concern to a more structured approach for evaluating AI within the organization. Not only did the RAF team leave with a shared understanding of AI opportunities and limitations in the context of their business, but it also increased its confidence in understanding the environmental and ethical implications.
An important insight that emerged during the workshop was the realization that there is no universal AI governance strategy or tool recommendation that works for every organization. While participants sought definitive answers about which tools to use or what policies to adopt, the conversations ultimately reinforced the importance of developing an approach that reflects RAF’s unique mission, values, and risk tolerance.
By creating space for honest discussion, practical evaluation, and values-based decision-making, Software for Good helped RAF build a stronger foundation for future AI exploration.