Two-thirds of American workers now support forcing AI companies to hand over half their stock to a government-controlled sovereign wealth fund, according to a June survey by Verasight released this week. The finding reflects growing anxiety over job security even as corporations pour billions into AI expansion and chip makers report capacity shortages stretching years into the future.
The Verasight survey of 1,690 adults found that 69% of Americans support "forcing" AI firms to transfer 50% of their stock to a public sovereign wealth fund. Benjamin Leff, chief executive officer of Verasight, said the public views such funds as "a tool to distribute the gains from the AI industry back to broader society."
Senator Bernie Sanders introduced the American AI Sovereign Wealth Fund Act this year, which would give the public a 50% stake in the largest AI companies in the U.S. Sanders said in a statement, "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 also said, "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 Job Loss Question
The proposal gains traction against a backdrop of significant workforce disruption. Goldman Sachs Senior Global Economist Joseph Briggs estimates that more than 9% of the labor force—around 15 million workers—could lose their jobs during a 10-year AI transition period, according to a report published last month. Briggs characterized this as "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."
However, the Goldman Sachs report notes Briggs believes those losses will prove temporary because AI will create many new jobs over the long term even as it destroys existing ones. This distinction matters: the survey capturing majority support for wealth redistribution reflects worker anxiety about near-term disruption, not necessarily acceptance that market forces will eventually rebalance employment.
Corporate Demand Outpaces Supply
Meanwhile, the actual AI infrastructure market tells a different story. A separate CNBC report published today indicates AI company executives see no signs of overcapacity in the buildout, even as enterprises scrutinize their return on investment. Chip stocks have surged over the past year as investors bet on semiconductors' central role in global AI infrastructure, though recent volatility has sparked debate about whether demand concerns are emerging.
Pat Gelsinger, former Intel CEO and now general partner at Playground Global, told CNBC on Wednesday, "I somewhat think of AI demand as almost unlimited," adding that energy availability is "the only real limiter." He continued, "Because how much economic value do you get for increased intelligence? Almost infinite across every industry imaginable."
Marc Boroditsky, chief revenue officer at Nebius, said, "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." Nebius is building data centers using Nvidia's GPUs.
Andrew Feldman, CEO of Cerebras Systems, pushed back against suggestions of industry overinvestment. 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—a company backed by Samsung and SK Hynix targeting a South Korea IPO next year—said, "AI infrastructure momentum [is] still huge," and stated, "I personally believe it's not the signal saying that … all the hyperscalers [are overinvesting] in the infrastructure."
Supply Chain Constraints
Michael Hurlston, CEO of Lumentum, offered perhaps the starkest indicator of demand strength. He said the 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," Hurlston 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.
This disconnect between worker anxiety and corporate expansion reveals a market in transition. 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 said, "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. He noted, "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."
Andrew Feldman suggested the market will naturally segment by workload. "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 69% support for forced AI wealth redistribution reflects legitimate worker concerns about technological displacement, yet the underlying market data suggests the private sector is managing demand and supply dynamics without crisis. The question facing policymakers isn't whether AI will disrupt labor markets—Goldman Sachs confirms it will—but whether government seizure of corporate assets represents sound policy versus a reaction to near-term anxiety. Corporate executives report sustained demand, sold-out capacity five years out, and energy as the binding constraint, not overinvestment. If those assessments prove accurate, mandating stock transfers could reduce capital available for the very infrastructure expansion needed to create future jobs. The tension between worker anxiety and market signals will likely shape AI policy debates heading into 2027.