Sen. Bernie Sanders, the Vermont independent, introduced legislation to create a $7 trillion AI sovereign wealth fund, financed by a one-time 50 percent equity tax on the largest artificial intelligence companies. The proposal would force firms like Google, Meta, and OpenAI to hand Washington an ownership stake in their operations, channeling future profits into direct payments to every American. The bill arrives as debate sharpens over who should benefit from AI-driven wealth and whether public ownership of private technology companies is a realistic policy tool or a deterrent to investment.
A 50 percent equity tax and the investment question
The core tension is straightforward: Sanders wants the federal government to take half the equity of the country’s biggest AI companies in a single stroke. That transfer would seed a federally managed fund designed to pay recurring dividends to citizens, similar to the way Alaska distributes oil revenue. The 2025 dividend program paid residents $1,000.00, a model Sanders has cited as proof that public ownership of resource wealth can work at scale.
The practical question is whether a levy of that size would slow the pace of AI spending. Google, Meta, Microsoft, and Amazon have each committed tens of billions of dollars to data centers, chips, and model training. A one-time seizure of 50 percent of equity would immediately reshape how boards and investors calculate returns on those outlays. If the policy were enacted, SEC filings within 18 months would likely show whether affected firms pulled back reported AI-related capital expenditures or restructured operations to limit exposure. That signal would be the clearest early test of the proposal’s real-world cost.
Supporters argue that the fund would generate returns without raising taxes on individuals. Critics counter that stripping half the ownership value from companies still racing to build frontier AI systems would discourage exactly the private capital needed to keep the United States competitive with China. Neither side has produced independent economic modeling of the tradeoff, leaving the debate anchored to competing assumptions rather than hard projections.
Sanders’ $7 trillion fund and its Alaska blueprint
Sanders’ office described the legislation as creating a national AI fund through a one-time 50% equity tax on the largest AI companies. The $7 trillion target figure reflects the combined market value Sanders’ team attributes to those firms, though the bill’s text would need to define which companies qualify and how equity valuations are assessed at the moment of transfer.
The Alaska comparison is useful but limited. Alaska’s fund draws on oil royalties paid over decades, not a single confiscation of corporate equity. The state’s dividend fluctuates year to year based on investment returns and political decisions about draws on the fund’s principal. Applying that model to AI companies raises a different set of questions: equity values swing with earnings forecasts, and a forced dilution event could itself depress the shares the government receives. No Treasury or congressional scoring of the proposal has been published, so the $7 trillion headline number has not been independently validated by federal budget analysts.
Sanders, who caucuses with Senate Democrats, has long pushed for wealth redistribution tied to corporate profits. His framing treats AI as a public resource comparable to oil or mineral rights, a position that resonates with voters worried about job displacement but also alarms investors who see AI as a nascent industry still absorbing heavy upfront losses. The senator argues that because AI systems are trained on publicly available data and research, the gains should not accrue only to shareholders and executives.
Under the bill, the federal government would hold equity stakes in qualifying AI firms and place those shares in the new fund. Dividends, buybacks, and eventual capital gains from stock sales would flow into a pool used to pay annual cash benefits to every American, regardless of income. Supporters say that structure would turn AI breakthroughs into a broad-based income stream rather than isolated windfalls in Silicon Valley and Wall Street.
Design details will determine how far the idea can go. Lawmakers would need to decide whether the equity tax applies only to U.S.-headquartered firms, how to treat foreign ownership, and what happens if companies spin off AI units or move intellectual property abroad. The bill would also have to address governance of the fund itself: who manages the assets, what investment rules apply, and how much political discretion exists to change payout formulas over time.
Legal challenges are almost certain. A 50 percent equity seizure would invite court fights over takings, due process, and the limits of Congress’s taxing power. Even if structured as a tax rather than outright nationalization, opponents would argue that singling out a narrow set of firms violates basic fairness and destabilizes expectations that underpin capital markets. Proponents respond that the extraordinary concentration of wealth anticipated from AI justifies an equally unusual policy response.
For now, the legislation functions as a marker in a larger argument about who owns the future of AI. Sanders is betting that public anxiety over automation, inequality, and tech power has reached a point where proposals once dismissed as fringe can shape the center of the debate. Whether or not his AI sovereign wealth fund advances in Congress, it forces lawmakers and industry leaders to confront a question that will not go away: if AI generates trillions in new value, how much of it should be treated as a shared national asset rather than a private prize?
David M. Keller is a finance writer based in Columbus, Ohio, covering personal finance and consumer-focused economic topics. He earned his degree in journalism from Ohio University and began his career reporting on local business and economic trends for a regional media outlet. Since then, he has contributed to a variety of online publications, focusing on clear, practical coverage of topics such as cost of living, debt, and everyday financial decision-making.
