{"id":4402231456588,"date":"2026-04-07T11:52:27","date_gmt":"2026-04-07T15:52:27","guid":{"rendered":"https:\/\/www.philanthropy.com\/?p=4402231456588"},"modified":"2026-04-08T11:37:53","modified_gmt":"2026-04-08T15:37:53","slug":"can-ai-make-grant-seeking-easier-and-grant-making-more-refined","status":"publish","type":"post","link":"https:\/\/www.philanthropy.com\/news\/can-ai-make-grant-seeking-easier-and-grant-making-more-refined\/","title":{"rendered":"Can AI Make Grant Seeking Easier and Grant Making More Refined?"},"content":{"rendered":"\n

The GitLab Foundation, the $30 million philanthropy of the AI software company with the same name, needed some extra brains to sort through all of the funding requests it received in September. It was offering a total of $4 million in grants to nonprofits testing ways to better use artificial intelligence to improve economic opportunity. So naturally the grant maker turned to its own AI systems to make sense of the 800 applications that flooded in.<\/p>\n\n\n

\n
\n
\n

<\/p>\n <\/div>\n

\n \"\" <\/div>\n
\n

How to Harness AI<\/a><\/h3>\n

The technology is bringing big change to all corners of the nonprofit world. Learn how fundraisers, grant makers, and leaders are using it to help them better meet their missions and fuel their organizations.<\/p>\n <\/div>\n <\/div>\n<\/div>\n\n\n

Reviewing such a big stash of applications would take GitLab\u2019s three program officers hundreds of hours without the aid of technology, said Ellie Bertani, GitLab Foundation\u2019s president. With an \u201caggressive\u201d use of AI to screen the applications, the whole thing took 30 minutes.<\/p>\n\n\n\n

Bertaini\u2019s team trained its AI tool to look at several criteria, including what kind of wage gains the applicants could produce, how strong their partnerships are, and what kind of data-security systems they have in place.<\/p>\n\n\n\n

Using AI to query large data sets allows Bertani to more easily observe trends in applications, including where resources may be most needed and how the foundation can fine-tune the questions it asks of grantees.<\/p>\n\n\n\n

GitLab Foundation\u2019s enthusiasm for AI makes it a bit of an outlier among grant makers. While many other foundations use the technology for aspects of their grant-selection process, only a small subset use the tools in an all-encompassing way, according to Chantal Forster, specialist in the use of technology in philanthropy who has consulted with more than a dozen foundations on AI use, including the Annenberg, Lumina, MacArthur, and Robert Wood Johnson foundations.<\/p>\n\n\n\n

Philanthropy technology experts like Forster envision foundations and nonprofits using AI to make applying for a grant faster. It could also help match grant seekers and grant makers with shared purposes and strong approaches to problem solving. A more radical use of AI and its ability to make sense of huge data sets could upend the entire grant-application process, resulting in a more automated system to bring nonprofits and foundations together.<\/p>\n\n\n

\n
\"\"
GitLab Foundation<\/div>
Ellie Bertani, president of the GitLab Foundation, says AI can screen a big stash of applications that would take the group\u2019s three program officers hundreds of hours. GitLab Foundation<\/figcaption><\/figure>\n<\/div>\n\n\n

At the GitLab Foundation, Bertani and her staff have fed troves of data from grant applications, grant reports, and check-in calls to a large language model that can respond to prompts, help identify patterns, and provide insights into things like common factors for success and failures among the 190 grants the foundation has made.<\/p>\n\n\n\n

\u201cIt helps us define our strategy going forward,\u201d she said, before adding that the responsibility for making actual grant decisions still rests with people, rather than a machine.<\/p>\n\n\n\n

Ultimately, the use of AI can help GitLab with its main job: getting money to nonprofits quickly, said Bertani.<\/p>\n\n\n\n

\u201cWe feel an acute responsibility to get the funds out the door as quickly as possible because we don\u2019t actually create impact; the grantees do,\u201d she said. \u201cAI can be really helpful in speeding up the process of insight gathering, making good bets, and getting the money out the door.\u201d<\/p>\n\n\n\n

AI Ambivalence<\/h2>\n\n\n\n

Foundation staff are using AI \u2014  Forster says that about 60 percent are trying out free tools like ChatGPT \u2014 but most grant makers don\u2019t have a formal plan for how to use it. The upshot, Forster said, is that grant makers don\u2019t have a handle on how AI is influencing their work and how it could best be used.<\/p>\n\n\n\n

\n

In many cases, foundation staff are leery about the use of AI because it may end up putting them out of jobs.<\/p>\n<\/blockquote>\n\n\n\n

In many cases, foundation staff are leery about the use of AI because it may end up putting them out of jobs, she says. As more philanthropies face pressure to push more money out the door to grantees, program staffers represent overhead costs that can be reduced with the use of technology tools.<\/p>\n\n\n\n

Cash-starved nonprofits, she said, face a different dynamic when considering AI.<\/p>\n\n\n\n

\u201cThey have real financial constraints,\u201d she said. \u201cThey want to use whatever tool they can use to get the job done\u201d and reduce costs.<\/p>\n\n\n

\n
\n
\n

Grappling With AI<\/p>\n <\/div>\n

\n

Many nonprofits are now using AI to better connect with donors, advance programs in ways that were once unaffordable, and drive efficiencies in grant making. And they foresee more potential uses as the technology improves.<\/p>\n

But AI is not without its downsides. Many nonprofit workers are concerned about its ethics and environmental impact. The vast majority of AI data centers are powered by electricity generated from fossil fuels, which contribute to climate change. A recent study from researchers at Cornell University found that by 2030, U.S. data centers will produce as much carbon dioxide as 5 million to 10 million cars and use as much water as up to 10 million Americans.<\/p>\n

And big tech firms often prevail over local opposition, as was the case recently in Mississippi, where local residents failed to block the installation of 41 gas turbines to power a data center for the AI platform Grok.<\/p>\n

But those concerns shouldn\u2019t be an excuse to avoid engaging with the technology, says Dan Kershaw, CEO of the Canadian nonprofit Furniture Bank. Corporations and governments are investing in the technology, and many nonprofit leaders do not want to be left behind. Using the simplest kinds of AI functions for the job at hand can minimize the impact, says CJ Orr, CEO of the Orr Group. For example, don\u2019t use deep research modes when a simpler approach that uses much less energy would do, he suggests.<\/p>\n

\u201cWe just recommend to folks that they are strategic about where and when they use it and minimize their footprint in the process,\u201d Orr says.<\/p>\n

\u2014Jim Rendon with reporting by Rasheeda Childress<\/p>\n <\/div>\n <\/div>\n<\/div>\n\n\n

When the Center for Effective Philanthropy surveyed nonprofits and foundations last spring, it found that grant makers did not have a clear view into how grantees could benefit from AI. More than 80 percent of foundations surveyed said their staff had little or no understanding of how AI could help grantees become more effective and had little idea of the technical capacity of grantees to use AI.<\/p>\n\n\n\n

Despite the uncertainty about how AI could help the grant-seeking process, the rapid growth of automated tools has put enormous pressure on nonprofits to incorporate them into their plans. Before doing so, suggests Jean Westrick, president of the Technology Association of Grantmakers, leaders should thoughtfully craft a plan.<\/p>\n\n\n\n

The use of technology won\u2019t reduce funding inequities unless people remain deeply involved, she said. And using it just to speed up decision making can lead to unintended consequences. Only human engagement can help ensure underrepresented organizations are discovered and supported, she said. What she\u2019d like to see is an application process that looks more like a dialogue between funder and grantee.<\/p>\n\n\n\n

\u201cThe application process is broken, and AI is not going to solve it,\u201d she said.<\/p>\n\n\n\n

AI Can Cause You to Overcommit<\/h2>\n\n\n\n

Last fall the Habitat for Humanity of Michigan held an AI training session for the 43 Habitat offices across the state. Wendy Clow, the group\u2019s director of operations, who led the sessions, was concerned about how or even whether the groups, which vary in size from two staffers to 70, were using the technology. <\/p>\n\n\n\n

She wanted to get everyone on the same page, and so she and a consultant provided training on AI policy, how to use AI to draft fundraising emails, and how to automate tasks like acknowledging donors, among other topics.<\/p>\n\n\n

\n \n
\n