New AI millionaires should fund existing nonprofits, not rebuild sector

The article opens with SpaceX's IPO this summer, which created an estimated 4,400 new millionaires overnight, with Anthropic and OpenAI expected to follow, driving Goldman Sachs' projection of a historic year for IPO proceeds. This abundance of new wealth raises an immediate question: how much will flow to people and communities in need? The authors—Max Simkoff, founder and CEO of Doma Technology and board director at JVS Bay Area, and Lisa Countryman-Quiroz, CEO of JVS Bay Area—describe seeing a country where costs are rising, services are stretched thin, and the American dream is further out of reach from both business and nonprofit vantage points.

They identify what they call an "alarming misapprehension" in tech circles: the belief that the nonprofit sector lacks the talent, speed, and ambition to deploy capital at scale. Tech entrepreneurs who came of age in the "move fast and break things" era want to apply that ethos to philanthropy, implying that the nonprofit sector needs rebuilding in tech's image. The authors directly contradict this premise. The U.S. has 1.8 million nonprofits operating right now, deploying roughly $600 billion in charitable giving each year. This sector has helped solve civilizational challenges like eradicating smallpox and lifting more than a billion people out of extreme poverty. Nonprofit workers are not well-meaning amateurs, the authors argue, but savvy operators with deep community knowledge and relationships that cannot simply be replicated.

To refute the idea that nonprofits are too rigid or set in their ways, the authors point to how the sector has survived decades of public funding cuts, shifting policy priorities, and economic volatility by learning to innovate, adapt, and do more with less. They argue that giving such organizations more to work with will yield even greater accomplishment. The strongest evidence comes from MacKenzie Scott's giving since 2019: more than $26 billion in large, unrestricted gifts to existing nonprofits. The Center for Effective Philanthropy studied outcomes over three years across more than a thousand organizations and found that 90% of recipients reported stronger financial positions, expanded programs, reduced staff burnout, and increased capacity to innovate. This undermines the early concern that nonprofits could not absorb capital at that scale.

The authors use workforce development as their primary example of how nonprofits are already responding nimbly to changing conditions. At JVS Bay Area, they have sunsetted job training programs in tech and developed new programs in sectors more resistant to automation, like healthcare and skilled trades. They have also integrated AI skills across all their training programs to help jobseekers remain competitive. Despite the uncertainty of 2025, their program graduates were still able to secure meaningful employment within less than a month on average. The implication is clear: nonprofits like JVS Bay Area do not need to invent a new way of putting capital to work; they simply need more funding for programs that are already proven effective.

The article concludes with a direct appeal to the next generation of tech philanthropists: before concluding that the nonprofit sector needs rebuilding, go look at what is already there. Meet the CEO of a workforce development organization, visit a community health clinic, ask an experienced program officer which organizations they would fund with twice the budget, or join the board of a nonprofit focused on a cause you care about. The core message is that the nonprofit sector has spent decades proving what is possible on a fraction of what it needed, and imagine how much more they can accomplish with new AI wealth behind them.