Nearly seven in ten Americans now support forcing the largest artificial intelligence companies to hand over half their stock to a public sovereign wealth fund—a striking show of public frustration as tech layoffs accelerate and corporate AI spending shows no signs of slowing.
A national survey of 1,690 adults by research firm Verasight, carried out in June and published earlier this month, found that 69% of Americans support "forcing" AI firms to transfer 50% of their stock to a public sovereign wealth fund. The timing matters. Workers are watching their colleagues disappear from payrolls while the companies eliminating those jobs pour billions into new infrastructure.
Benjamin Leff, chief executive officer of Verasight, explained the public's calculation plainly: "In the eyes of the public, AI Sovereign funds are seen as a tool to distribute the gains from the AI industry back to broader society."
Senator Bernie Sanders moved this sentiment from polling data into legislative action. In June, he proposed the American AI Sovereign Wealth Fund Act, which, if passed, would give the public a 50% stake in the largest AI companies in the U.S. Sanders framed the stakes in stark terms: "It would guarantee that the economic benefits generated by AI are used to improve the lives of all of us — not simply to make the richest people in the world even richer." He added a warning about power: "The future of AI and the fate of humanity must not be decided behind closed doors in Silicon Valley by billionaires seeking to maximize their power and profit."
The Human Cost of Automation
The urgency behind these proposals is rooted in real job losses. Goldman Sachs Senior Global Economist Joseph Goldstein estimates that more than 9% of the labor force, or around 15 million workers, could lose their jobs during a 10-year AI transition period, according to a report published last month. Goldstein placed this in historical context: "This would be the type of automation and reallocation shock that we saw in the late '90s and early 2000s and in other periods of significant technological change."
The Goldman Sachs analysis suggests these losses will prove temporary because AI will create many new jobs over the long term. But that cold comfort rings hollow for workers facing immediate layoffs. They're being asked to absorb the disruption while corporations reap the gains.
Corporate Spending Continues Unabated
Meanwhile, the companies shedding workers aren't pulling back on AI investment. A separate CNBC report published today said AI company executives are not seeing signs of overcapacity in the AI buildout, even as enterprises scrutinize how much AI costs and what return they're actually getting.
Pat Gelsinger, the former Intel CEO and now general partner at Playground Global, told CNBC on Wednesday that he views AI demand as "almost unlimited," with energy availability being "the only real limiter." He argued: "Because how much economic value do you get for increased intelligence? Almost infinite across every industry imaginable."
Marc Boroditsky, chief revenue officer at Nebius, which is building data centers using Nvidia's GPUs, said simply: "What we're experiencing in terms of demand is extraordinary. There's much more demand than we're able to fulfil, and that's been our experience for some time now."
Andrew Feldman, CEO of Cerebras Systems, pushed back against the idea that the industry is overbuilding. He said the example of Meta and xAI selling excess capacity is a "unique" case, adding: "For the industry as a whole, the demand for compute far outstrips available capacity, and we're short on data centers. I think we're short on, as an industry, many of the inputs to compute."
Sungyun Park, CEO of Rebellions, which is backed by Samsung and SK Hynix and targeting an IPO in South Korea next year, said: "AI infrastructure momentum [is] still huge," and added, "I personally believe it's not the signal saying that … all the hyperscalers [are overinvesting] in the infrastructure."
Michael Hurlston, CEO of Lumentum, offered perhaps the clearest picture of demand intensity. His company's products are sold out for the next five years. "We're trying to build up our capacity as much as we possibly can to fulfil a demand that we see out five years at this point," he said. Lumentum's stock is up around 600% over the last 12 months as investors pile into companies addressing key bottlenecks in the buildout of AI data centers.
A Shift Toward Accountability
One modest sign of rationality emerged in how companies are now deploying AI. Enterprises are moving away from so-called "tokenmaxxing," a period when companies encouraged employees to use as much AI as possible regardless of results, often with tools from frontier labs like OpenAI and Anthropic. Companies are now focusing more on return on investment from AI, especially as frontier models remain expensive relative to open source offerings from companies like DeepSeek or Alibaba.
Boroditsky captured the shift: "The CFO bringing the hammer down and slowing spend should actually be looking for value or valuemaxxing," adding that AI should be applied to create value that justifies the spending. "We're seeing a shift now to more rationalization. We've seen it with every tech cycle, and that rationalization will definitely continue the demand."
Feldman predicted future AI use will split by workload, with frontier models used for advanced problems and other models handling easier tasks. "I think it's probably the case that you don't need a giant bus to go to the grocery store," he said. "Certain workloads migrate to some type of compute and easier workloads to others, and I think as we learn and become more sophisticated in our deployment of AI, the same thing will happen."
Why This Matters:
The gap between public concern and corporate behavior is widening. Americans are watching AI companies eliminate jobs while simultaneously spending at unprecedented levels to expand their capacity and dominance. The 69% support for a sovereign wealth fund reflects a basic intuition about fairness: if AI is generating extraordinary wealth for a small number of corporations and their shareholders, shouldn't the public—especially workers bearing the cost of transition—share in those gains? The Goldman Sachs estimate of 15 million potential job losses over a decade underscores why this isn't abstract. Without mechanisms to distribute AI's benefits or support displaced workers, the technology risks deepening inequality rather than broadly improving living standards. Sanders' proposal and the Verasight survey suggest Americans aren't content to trust that "new jobs" will materialize for those losing theirs today. They're demanding a structural solution—public ownership stakes that would fund social investment and ensure the gains from AI advancement benefit more than the billionaires currently controlling the technology.