
Tech • IA • Crypto
Proposals in the United States to grant the government equity stakes in major AI firms could mark a historic shift toward state participation in AI revenues.
Discussions have emerged around the U.S. government taking an equity position in leading artificial intelligence companies such as OpenAI and Anthropic. The idea would involve granting shares to the state rather than a direct purchase, allowing public finances to benefit from AI-driven profits without upfront taxpayer cost.
This approach echoes earlier intervention with Intel, where federal support was tied to strategic influence and financial return. While not a formal nationalization, such arrangements resemble a hybrid model in which private firms remain independent but share ownership with the state.
Advocates, including figures in the tech sector, argue that AI-generated wealth should partly flow back to citizens. Government shareholding could channel revenues into public spending, potentially funding services like healthcare, pensions, or infrastructure through dividends tied to AI growth.
Because AI companies operate globally, revenues derived from international users could indirectly contribute to U.S. public finances. This raises concerns abroad, as consumers and businesses outside the United States might effectively support American state programs through their spending on AI services.
The concept has drawn attention across the political spectrum. While associated with interventionist economic policies, similar ideas have been supported by figures on both the right and left, including calls for significant public capture of AI profits as a “common good.”
Beyond revenue, government ownership could ensure influence over a technology seen as foundational to economic and military power. AI is increasingly viewed as comparable to energy or semiconductors in strategic importance.
Granting the U.S. government equity in AI firms would redefine the relationship between state and technology, with far-reaching economic and geopolitical consequences.