SpaceX's initial public offering this summer generated an estimated 4,400 new millionaires overnight, with Anthropic and OpenAI widely expected to follow a similar path. Goldman Sachs projects a record-breaking year for IPO proceeds, fueled by the artificial intelligence boom. The central question is how much of this vast new wealth will ultimately reach those who need it most.

This is not the first time a wave of technology-generated wealth has prompted debate over how best to direct philanthropy. The dot-com boom of the late 1990s and the social-media era that followed each produced a generation of young philanthropists who questioned whether traditional nonprofits could move fast enough. In recent years, the effective altruism movement, rooted in Silicon Valley, has further pushed the idea that data-driven, venture-style approaches can outperform established charitable institutions. The current AI wealth cycle intensifies that conversation.

The authors of this commentary bring two distinct perspectives: one as a builder and scaler of technology companies, the other as the leader of a nonprofit providing career training to help people reach the middle class. From both vantage points, they observe a country where costs are climbing, social services are stretched thin, and the American dream is increasingly out of reach.

While AI-generated wealth could help address these challenges, a troubling misconception has taken hold in tech circles — the belief that the nonprofit sector lacks the talent, speed, and ambition necessary to deploy capital at scale. Professionals shaped by the "move fast and break things" ethos want to apply that same philosophy to philanthropy, effectively rebuilding the sector in tech's image.

In reality, the United States does not need an entirely new infrastructure to channel AI wealth effectively. There are currently 1.8 million nonprofits operating across the country, collectively deploying approximately $600 billion in charitable giving annually to improve lives and communities. This sector has historically tackled civilizational-scale challenges, including the eradication of smallpox and the lifting of more than a billion people out of extreme poverty. Contrary to popular perception, nonprofit professionals are not well-intentioned amateurs waiting for the tech industry to rescue them — they are seasoned operators with deep community knowledge and relationships that cannot be easily replicated.

Nonprofit organizations have weathered decades of public funding reductions, shifting policy priorities, and economic volatility. Much like their counterparts in technology, they have learned to innovate, adapt, and deliver more with fewer resources. Providing them with greater funding would enable them to scale their impact accordingly.

The evidence that nonprofits can absorb transformational investment is already well established. Since 2019, MacKenzie Scott has distributed more than $26 billion in large, unrestricted gifts to existing nonprofits. The Center for Effective Philanthropy conducted a three-year study of the outcomes and found that 90% of recipient organizations reported stronger financial positions, expanded programs, reduced staff burnout, and an increased capacity to innovate. Earlier concerns that nonprofits could not manage capital at that scale proved unfounded across more than a thousand organizations.

The notion that nonprofits are too rigid to respond to a rapidly changing world also fails to withstand scrutiny. The most effective nonprofits function much like technology startups — continuously assessing conditions and redirecting resources to where need is greatest. This responsiveness is driven partly by necessity, as nonprofits must remain attuned to evolving community needs and shifting donor priorities. Many organizations are required to raise their entire operating budget from scratch each year, a pressure that fosters operational discipline and adaptability.

Workforce development is the area where this dynamic is most visible today, and where AI-generated wealth carries perhaps the greatest responsibility. As the labor market undergoes rapid transformation, demand for career training programs has risen sharply. With generative AI reshaping employment patterns, workforce-focused nonprofits have continued to innovate. At JVS Bay Area, for example, the organization has phased out job training programs in technology and developed new ones in sectors more resistant to automation, such as healthcare and the skilled trades. AI skills have been integrated across all training programs to help jobseekers remain competitive. Despite the uncertainty that characterized 2025, program graduates secured meaningful employment in less than a month on average.

Organizations like these do not need to invent new methods for deploying capital — they require additional funding for programs already proven effective. Across the country, countless nonprofits have established track records of nimble, effective work on a wide range of pressing social issues. What they share is a funding gap that AI-era philanthropy is uniquely positioned to close.

The message to the next generation of tech philanthropists is straightforward: before concluding that the nonprofit sector requires a wholesale rebuild, examine what already exists. Meet with the leadership of a workforce development organization. Visit a community health clinic. Consult an experienced program officer at an established foundation about which organizations they would support with a doubled budget. Join the board of a nonprofit dedicated to a cause of personal importance.

The nonprofit sector has spent decades demonstrating what is achievable with only a fraction of the resources it actually needs. With new AI wealth behind it, the potential for impact is considerably greater.

Max Simkoff is the founder and CEO of Doma Technology and a board director at JVS Bay Area. Lisa Countryman-Quiroz is CEO of JVS Bay Area.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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