Created By: Terry CangelosiSeptember 23, 2025 You’re not the only one wondering about the environmental cost of AI. As more nonprofits explore these tools, questions about their climate impact are growing louder, and rightfully so. AI tools offer significant potential to improve nonprofit workflows, but like any technology, they come with tradeoffs. AI’s environmental footprint is one of the most pressing concerns we hear when talking to our nonprofit partners. As AI gets more embedded into our day-to-day tasks, it’s natural to wonder about the climate cost of this new technology. We want to offer both context and clarity. Yes, AI has an environmental impact. But if used thoughtfully, nonprofits can keep their footprint small while maximizing the benefits to their mission and the communities they serve. AI’s Footprint, in Context In 2023, data centers accounted for roughly 4.4 percent of all electricity used in the U.S. That number includes the energy required to run cloud storage, websites, email servers, streaming platforms, business applications, and more. AI is a growing part of that total, but currently only makes up an estimated 14 percent of data center workloads. So, while AI’s footprint is increasing, it remains a fraction of the overall energy used to power the digital tools we rely on daily. The good news is that the AI activities most common for nonprofits, such as summarizing notes, drafting an email, or brainstorming fundraising ideas, represent an even tinier fraction of that footprint. These tasks are more comparable to flipping on a lightbulb than powering a full office building. AI Can Help Reduce Emissions Elsewhere It is also important to consider the full picture. If AI helps your organization deliver services more efficiently, reduce paper use, or avoid unnecessary travel, those outcomes can minimize emissions in other areas. Weighing environmental impact alongside mission impact is critical. In many cases, smart use of AI can support environmental goals. For example: A food bank might use AI to optimize truck delivery routes, reducing fuel consumption. A volunteer coordinator might use AI to automate scheduling, limiting back-and-forth communications and unnecessary staff travel. A program team might use AI to analyze large datasets faster, accelerating response times and more quickly advancing the mission of the organization. These applications help reduce inefficiencies that might otherwise require more energy, time, or manual resources to resolve. Four Steps Nonprofits Can Take to Reduce Their AI Carbon Footprint While the average nonprofit’s use of AI is unlikely to significantly impact the environment, there are still ways to reduce your digital footprint and use AI more thoughtfully. 1. Create a Responsible AI Usage Policy We’ve written about this at length, but there is a reason for that. This is the first step to aligning your organization around a shared understanding of how AI should be used. A simple, responsible AI usage policy can guide staff to use AI where it adds the most value, avoid overuse for minor tasks, and share effective prompts and resources to reduce mistakes. These practices promote both impact and efficiency, and you don’t need to be a tech expert to get started. Your policy should focus on values, boundaries, and expectations—and once finalized, be shared publicly to promote transparency and ethics. 2. Train Staff to Use AI Efficiently The more fluently your team can use AI tools, the less time and energy they’ll waste. Embedding AI education into your existing learning and development programs can help staff avoid repetitive queries, improve prompt quality, and limit unnecessary tool usage. Encourage staff to experiment with AI to address lighter-weight tasks and invite them to share tips. Simple lunch-and-learns and educational channels can go a long way toward building shared AI practices that are both efficient and effective. 3. Choose Lower-Impact Tools Not every AI system requires high computing power. Many tools already in your workflow are built on lightweight models designed to do more with less. For example, GPT-4o is optimized to run more efficiently and faster for everyday tasks. Smaller models like DistilBERT are commonly used in tools built for nonprofits and are intentionally designed to be lower energy. Choosing the right tool for the task can help you stay efficient and reduce energy use without sacrificing performance. 4. Work With the Right Partners If your organization is unsure how to assess tools or design policies, consider working with a trusted partner. Orr Group, for example, helps nonprofits evaluate their existing workflows for inefficiencies, build responsible usage frameworks, and train teams on how to use AI to maximize value while minimizing unintended consequences. Expert support can help you avoid overbuilding or overspending while helping you make sustainable decisions that align with your mission. Use AI with Purpose The climate crisis is real, and nonprofits are right to ask hard questions about the tools they use. AI can be an incredible asset, but it is not without its impact. The key is to use it intentionally. That means staying informed about the footprint of new tools. It means educating teams and setting thoughtful policies. And it means balancing energy use with the potential to expand access, reduce waste, or drive mission-critical outcomes. The good news is that nonprofits can lead by example here. While your day-to-day use of AI is unlikely to create a major spike in emissions, how you use it (and why) can send a powerful message. Responsible technology use is not just about reducing harm. It is about using your resources wisely, in service of the greater good. At Orr Group, we’re enthusiastic about the future of AI and hope to share that enthusiasm with our nonprofit partners. We are ready to assist your organization in assessing your workflows and implementing AI & automation into your fundraising and other operational efforts. Contact us to learn how we can help elevate your organization. Contact Us Terry Cangelosi is a Senior Director and Head of Operations at Orr Group. Terry brings 10+ years of nonprofit operations experience to ensure the most efficient operations in Orr Group’s workflows, technology, and infrastructure. Terry is a member of Orr Group’s AI Taskforce.
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