Artificial Intelligence (AI) is a hot topic these days – and a lot of advocates are wondering how we can navigate these emerging technologies and tools effectively, ethically, and in line with our values.
At the Lab, our mission is to serve the climate community with evidence-based insights. This includes supporting this community with the best research and training available to make effective, evidence-based, and responsible use of AI. We’ve gathered some high-quality resources here, with more to come.
Join our Climate Movement AI Landscape Analysis by taking our survey or letting us know you’re interested in participating in an interview or focus group.
AI: Artificial intelligence, or any branch of computer science that involves training computers to think like humans. When you use the spelling or grammar check in Google Docs, or talk to Siri, that’s AI.
Generative AI: AI that can create language, code, or images. Think of those images you see on social media with 6 fingers, or the way ChatGPT can help you write a difficult email.
Predictive AI: AI that uses past data to predict what will happen in the future. Think of social media algorithms that decide what videos to show you based on how you’ve interacted with other content.
LLM: Large Language Models, or AI that can interpret normal human language and generate a response in human language. Think of ChatGPT or Google’s Gemini.
Prompts: These are the requests you make of an LLM. For instance, if you ask Claude (an LLM) for the best way to grill salmon, or where you should go on vacation, those are prompts.
Training: This is how AI models “learn” to understand and analyze language or other data. For instance, LLMs like ChatGPT are “trained” on vast amounts of text found online.
For a deeper dive on AI terminology, check out The Verge’s AI terminology explainer.
Several other respected organizations have gathered resources, toolkits, and articles to guide nonprofits in navigating the landscape of AI.
NTEN’s AI for Nonprofits Resource Hub: The Nonprofit Technology Network has developed a robust set of articles and videos, with an emphasis on nonprofit governance. Topics include governance frameworks, data privacy, and tools evaluation.
Georgetown University’s AI Toolkit for Nonprofits: This toolkit includes a self-assessment, a framework for how to use different tools, and a breakdown of recommended tools.
The Whole Whale Guide to Practical AI: Unlike the other two hubs, this guide focuses on how nonprofits can use AI tools effectively.
One of the biggest challenges facing nonprofit leaders right now is how to balance the opportunities and risks inherent in AI technology, in ways that honor your organizations’ mission and values, respect your staff, protect your supporters’ privacy, and safeguard your organization’s intellectual property. This is especially fraught for organizations that work on climate, as we learn more about the impacts of AI on our climate and environment.
Developing your own organization’s policies will take a lot of internal conversation and work. But these templates and guides provide a good starting point for those conversations.
NTEN’s AI for Nonprofits Resource Hub: We’re mentioning this site again because it has such good videos and other resources for developing your organization’s AI governance and policies.
Should My Nonprofit Use AI? Great FAQ from Whole Whale.
ANB Advisory’s AI Template: This guide offers both a template and a guidebook for developing your own policy.
The Framework for Responsible and Beneficial AI for Fundraising: This was published by the Fundraising.AI collaborative, a group of fundraisers working to define responsible AI use for fundraising teams.
10 AI policies you can use as a template: These policies come from a wide variety of sectors, and may give you ideas of areas to focus on that you haven’t even thought about.
LLMs are often seen as the entry-point into AI for many organizations. And many of us are already using LLMs in our work and personal lives. Below are some resources to help guide safe and strategic implementation.
Dos and Don’ts for Generative AI tools: Guidance for using generative AI responsibly.
Fundraising: AI for Nonprofits: A compendium of tips for using AI with a focus on fundraising.
Questions to ask Generative AI vendors: A list of thoughtful questions to help you make the best and most responsible decisions.
One of the biggest challenges in using LLMs effectively is writing prompts (or requests) that result in strong results. These guides help you understand how LLMs “think” and how to write effective prompts.
Whole Whale Writing Prompt Formula: This resource offers a really helpful framework for HOW to write prompts.
Nonprofit Gemini Prompt Library: This was created by Google for its LLM, Gemini, but offers helpful prompts for a lot of common non-profit uses.
The Prompt Collection: This is a collection of slides from a presentation about how to write LLM prompts. It’s not specific to non-profits or advocacy work, but it’s a very helpful guide.
Below are some research reports on how nonprofits are (or are not) adopting AI.
Techsoup: the State of AI in Nonprofits 2025
Inspiring Action: Identifying the Social Sector AI Opportunity Gap
How is your organization using AI?
We want to hear from you as we develop our training series! How is your organization using AI now? What questions are you wrestling with? What do you want to learn more about? Do you have a great example of how you developed your AI policy, or used AI in a really effective way? Let us know by emailing Raz Pollex or connecting on the Climate Advocacy Lab Community Slack!