OpenAI and Anthropic, founded by AI developers who feared unrestrained corporate AI development, were each co-opted by market incentives and became corporate behemoths guarding investor value rather than the public interest. In June, both companies filed for their IPOs and were met with buzz about trillion-dollar valuations, prompting proposals for the federal government to seize stock for a US sovereign wealth fund or redistribute revenues as taxpayer dividends. Now, headlines focus on public backlash to AI datacenters and Nvidia’s slumping stock, while SpaceX’s newly minted stock price tanked weeks after its IPO, and questions arise about whether leading AI labs will ever be sustainably profitable. Evidence suggests the market could reassess that these companies offer nothing of financial value. If they fail in financial markets, the US should nationalize them and convert them into national labs operated under democratic control to preserve public benefit. The economics of big AI labs hardly guarantee booming returns: frontier models are expensive to train and depreciate within months, narrowing the payback window. Enterprise clients minimize AI token usage, models are commodities with similar performance, and open-source and Chinese competitors lagging only a few months behind give away free models. Many free and open-source models can be run locally, on private clouds, high-end servers, laptops, or cellphones, questioning the companies’ profitability.