Artificial intelligence is already part of many foundations’ daily work. From drafting emails to summarizing documents, funders are experimenting with AI tools to save time and reduce administrative burden. As adoption grows, so do essential questions: How can we use AI responsibly? What are the implications for data privacy and bias? And how can funders ensure these tools support more equitable grantmaking rather than undermine it?
At Exponent Philanthropy’s 2025 Annual Conference, I shared a practical, funder-focused approach to using AI thoughtfully, balancing opportunity with caution and keeping equity front and center. This article distills those ideas into clear, actionable guidance for lean funders ready to move forward with confidence.
What Do We Mean by “AI,” Really?
At its core, AI refers to systems that can perform tasks we usually associate with human intelligence, recognizing patterns, summarizing information, or generating ideas. Most of us already interact with AI every day, whether we realize it or not. Autocorrect, streaming recommendations, voice assistants, and chatbots are all familiar examples.
In philanthropy, AI is showing up in practical, accessible ways. Foundations are using it to draft communications, summarize grant applications, or brainstorm language. These “low-hanging fruit” use cases are often where organizations start and where they can see immediate value with relatively low risk.
AI Adoption Is Widespread but Still Early
Recent research shows that 81% of funders report some level of AI use. At the same time, deep integration remains uncommon. Most organizations are still experimenting rather than embedding AI into core workflows.
That’s not a bad thing. In fact, this early stage creates a significant opportunity. Before habits become entrenched, foundations can shape how AI is used by putting clear guardrails in place and aligning tools with values from the start, rather than trying to course-correct later.
Legal and Data Considerations: Read the Fine Print
One of the most critical and often overlooked steps in using AI responsibly is understanding a tool’s terms of use. Before uploading any information, funders should pause and ask a few basic questions:
- Does this tool store what I upload?
- Is my data used to train future models?
- Can I delete my data later?
For example, pasting a confidential grant proposal into a public AI tool could unintentionally expose sensitive information. As a general rule, funders should avoid sharing identifying or confidential data unless they are confident the tool is private and secure. Enterprise or paid versions of AI tools often offer stronger protections and clearer data controls.
It’s also important to be explicit about who has access to AI tools tied to organizational data and where that data is stored. Tools that are U.S.-based or EU-compliant tend to have stronger privacy safeguards.
Centering Equity in AI Use
AI systems reflect the data they are trained on, and that data often contains historical bias. Without intention, AI can quietly reinforce inequities rather than help address them.
Before adopting a new AI use case, funders should step back and ask:
- Who might be left out by this approach?
- Could this introduce bias into decision-making or processes?
- Does this make things easier for grantees as well as funders?
- Are we using AI to reduce barriers, such as language or accessibility challenges?
Equitable AI use isn’t about how advanced the technology is; it’s about why and how it’s used. When applied thoughtfully, AI can simplify processes, clarify expectations, and reduce administrative friction. Used carelessly, it can add complexity and create distance.
A Simple Framework To Begin
For organizations unsure where to start, a lightweight framework can help guide early decisions:
- Comfort – Begin with internal alignment. What data are you comfortable sharing outside your organization? Where should humans always remain in the loop? Naming boundaries upfront builds clarity and trust.
- Terms – Understand how specific tools handle data. Look for features like private mode or no data retention and start by testing AI with low-stakes tasks such as drafting internal communications.
- Policy – Write it down. An AI use policy doesn’t need to be long or technical—it just needs to set expectations and reinforce commitments to equity, transparency, and accountability.
Using AI To Reduce (Not Add To) Administrative Burden
The most promising uses of AI in philanthropy are not about replacing judgment or decision-making. They’re about freeing up time.
Practical AI Tools Funders Are Using Today
Tasks like summarizing long reports, drafting first-pass communications, or organizing notes can quietly consume staff capacity without adding proportional value. When used well, AI can take on this work, allowing teams to spend more time on relationships, learning, and impact.
ChatGPT and Claude
These large language model tools help users generate content, analyze information, and work through complex ideas using natural language. Foundations use them to draft grant descriptions, summarize and analyze grantee reports, research issue areas, and sketch early program strategies or theories of change. The benefit is straightforward: faster writing and synthesis without adding headcount.
Scribe
Scribe automatically records on-screen workflows and turns them into step-by-step guides with screenshots and text. Funders use it to quickly and clearly create articles like “How to Apply” guides for grantees, onboarding materials for board members, and internal process documentation.
AI-Powered Language Translation
Language translation is one area where AI is particularly strong. Many grants management platforms, including Temelio, now use AI to translate grantee forms, helping make applications more accessible to a wider range of organizations. You can see this tool in action here.
Moving Forward Thoughtfully
AI is not a silver bullet, but it is a powerful tool, especially for lean funders working with limited resources. The key is to move forward with intention: understand the risks, center equity, and start small. When used as a support rather than a substitute for human judgment, AI can help philanthropy work more efficiently while staying true to its values.
AI in Action: Tools and Tactics for Smarter, More Equitable Giving
/ Webinar
This hands-on session includes a brief overview of AI use in philanthropy, core guardrails to consider with AI use, and a demo of three free AI tools. Learn more.
About the Author
Maya Kuppermann is the co-founder and CEO of Temelio, a grantmaking and impact management platform. She works closely with philanthropic organizations to improve data practices, streamline operations, and support more equitable and effective giving. Maya regularly speaks and writes about the responsible use of technology in philanthropy.