AI’s new millionaires want to disrupt philanthropy. They should fund what already exists
AI's newly minted millionaires should keep their "move fast and break things" ethos far away from philanthropy.
The recent IPO of SpaceX has created an estimated 4,400 new millionaires, and other AI companies like Anthropic and OpenAI are set to follow suit. A significant amount of this AI wealth could potentially be redirected to address the needs of those in need. However, there exists a misconception within tech circles that the nonprofit sector lacks the necessary talent, speed, and ambition to effectively deploy this capital.
In reality, there are 1.8 million nonprofits operating in the U.S., contributing roughly $600 billion annually in charitable giving. These organizations have proven their effectiveness in solving complex issues such as eradicating diseases and lifting people out of extreme poverty. Nonprofit workers are seasoned operators who have demonstrated adaptability and innovation in the face of public funding cuts and shifting priorities.
They have already benefited from substantial unrestricted gifts, such as those from MacKenzie Scott, which have resulted in stronger financial positions, expanded programs, and increased capacity for innovation. The assumption that nonprofits are unable to absorb capital at this scale has been proven false, with over a thousand organizations successfully managing substantial increases in funding.
Nonprofits operate similarly to tech startups, constantly adapting to meet community needs and donor focus. Workforce development is particularly urgent as AI reshapes the job market, and nonprofits have already shown their ability to integrate AI skills into existing programs to better prepare jobseekers. There is a significant funding gap for nonprofits to address urgent social issues, and AI philanthropy could step in to fill this gap.
The solution does not require reinventing the nonprofit sector, but rather providing more funding for proven effective programs.
Written by urgent.news from Fortune's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.