📊 Full opportunity report: The United States: The High-Variance Bet on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
The US is betting on minimal regulation and market-driven growth in AI, with a fragmented social safety net. This approach prioritizes innovation and ownership, but leaves gaps in national policy.
The United States has adopted a deliberate strategy of minimal regulation for artificial intelligence and social welfare, emphasizing market dynamism over government oversight. This approach aims to foster innovation and ownership, positioning the country as a leader in AI development and economic growth.
Since January 2025, the US administration has revoked previous AI oversight policies and replaced them with a stance favoring minimal regulation, seeking to maintain American leadership in AI. In July 2025, the White House released an ‘AI Action Plan’ that prioritizes competitiveness through deregulation. By December 2025, executive orders empowered the Department of Justice to challenge state-level AI laws and prevent burdensome regulations, with plans to preempt state laws outright by March 2026.
Meanwhile, the social safety net remains fragmented and limited at the federal level. The Earned Income Tax Credit (EITC) provides support only for working families with children, with no universal income guarantee. Instead, local governments are pioneering guaranteed-income pilots, such as Stockton and Cook County, which have implemented or made permanent monthly payments of around $500. These city-led initiatives operate independently of federal policy, filling the void left at the national level.
This strategy reflects a core belief: that fostering the engine of innovation—through deregulation, flexible labor markets, and private ownership—will generate the wealth necessary to support future redistribution, even if the federal safety net remains minimal.
The High-Variance Bet
The country building the disruption made the most distinctive choice of all: bet on the dynamism, regulate it least — even block others from regulating it — and tie the floor to work. The thinnest row on the map.
Independent commentary, produced with AI assistance under human editorial oversight. The views are the author’s own and may change. This is analysis, not policy, economic, investment, or legal advice. Descriptions of US federal AI executive actions, the EITC, “Trump accounts,” and municipal guaranteed-income pilots reflect publicly reported information as of mid-2026 and may change as litigation and legislation evolve. This phase maps differing approaches and endorses none; characterizations of contested policies present competing views, not a verdict, and references to specific administrations and programs are factual and analytical, not partisan. Country and program names are referenced for analysis and imply no affiliation.
Implications of the US’s Deregulatory, Market-Led Strategy
This approach signifies a fundamental shift in how the US aims to compete economically and technologically. By prioritizing innovation and ownership, the country seeks to maximize growth and wealth creation, betting that the benefits will trickle down to support social needs in the future. However, the minimal federal safety net and the reliance on city-level pilots raise concerns about inequality and the ability to support vulnerable populations during economic transitions, such as AI-driven labor shifts.
Internationally, this strategy contrasts sharply with Europe and Nordic countries, which implement heavier regulation and broader social protections. The US’s stance may influence global AI governance and economic models, potentially setting a precedent for deregulation as a competitiveness tool.
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US Policy Shift and the Rise of Local Experiments
Historically, the US has favored market-led innovation, but recent policy moves mark a decisive turn towards deregulation, especially in AI. Starting with the revocation of oversight policies in early 2025, the administration has consistently pushed for minimal regulation, framing it as a means to maintain technological and economic dominance.
Simultaneously, the federal social safety net remains limited, with programs like the EITC serving only specific populations. In contrast, over 150 cities and counties have launched guaranteed-income pilots, experimenting with direct cash payments to address economic insecurity caused by automation and AI. These local initiatives are largely independent of federal policy, reflecting a decentralized response to the national void.
This pattern of top-down deregulation and bottom-up social experiments underscores the US’s unique approach to building its future economy, emphasizing flexibility, private ownership, and innovation-driven growth.
“The US will preempt state AI laws to ensure American leadership and maintain a regulatory environment conducive to innovation.”
— White House policy document, March 2026
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Unclear Long-Term Outcomes of the US Approach
It remains uncertain whether the minimal regulation strategy will sustain long-term economic growth and social stability. The effectiveness of city-led guaranteed-income pilots as a scalable solution is still unproven, and the potential consequences of a fragmented social safety net are not fully understood. Additionally, the global impact of the US’s deregulation-driven model on international AI governance is still developing.
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Federal authorities are expected to continue preempting state AI laws and refining their deregulatory stance through legislative and executive actions. Monitoring the expansion and outcomes of city-level guaranteed-income programs will be critical to assessing the social impact of this decentralized approach. Internationally, other countries may adopt similar strategies or respond with increased regulation, shaping the future global landscape of AI governance and social policy.
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Key Questions
Why is the US avoiding regulation of AI?
The US believes that minimal regulation will foster innovation, maintain its global leadership in AI, and maximize economic growth, trusting that wealth will eventually support social needs.
Are city-level guaranteed-income programs effective?
These programs are still experimental and localized, with some showing promise, but their long-term effectiveness and scalability remain uncertain.
What risks does this strategy pose?
The primary risks include increased inequality, insufficient support for vulnerable populations, and potential challenges in managing societal impacts of rapid technological change without comprehensive federal safeguards.
How does this compare to European approaches?
European countries tend to implement heavier regulation and broader social protections, contrasting with the US’s market-led, deregulated model aimed at maximizing innovation and ownership.
Source: ThorstenMeyerAI.com
