The United States is set to push G20 countries towards a lighter-touch approach to artificial intelligence at a two-day meeting in North Carolina beginning September 1. US technology adviser Michael Kratsios is expected to promote the “Carolina Principles,” which call for new AI rules only where existing laws do not address emerging risks, while encouraging investment in foundational research and commercial development.
The meeting brings together commerce ministers and some of the biggest names in technology, including OpenAI CEO Sam Altman, Nvidia CEO Jensen Huang, Meta CEO Mark Zuckerberg, Google DeepMind co-founder Demis Hassabis and SpaceX CEO Elon Musk. The discussions come as Washington and Beijing compete for AI leadership and countries continue to take very different approaches to regulating the technology.
U.S. to Advocate for Hands-Off AI Rules at G20
The United States will encourage G20 members to take a hands-off approach to AI regulation during a meeting in North Carolina. Officials will promote the Carolina Principles, aiming to avoid introducing new regulations for the… pic.twitter.com/Q3Eg6h7mnY
— Ploutos (@Ploutos97) September 1, 2026
Could the Carolina Principles become a model for AI policy?
The Carolina Principles argue that policymakers should use existing laws wherever possible and create new rules only for issues that are genuinely new. That could prevent governments from creating separate regulations every time AI enters another industry. A bank using AI for fraud detection, for example, could remain under existing financial and data laws rather than facing an entirely new AI regime. The approach also has a practical advantage for companies operating across borders. If countries adopt similar principles, businesses would have fewer overlapping rules to deal with as they develop and deploy AI in different markets.
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However, AI does not always fit neatly into existing laws. An AI agent that can write and execute code, make decisions, and act without constant human input can create risks that older rules were never designed to address. Recent incidents involving AI systems hacking websites have already raised questions about where existing cybersecurity rules stop, and AI-specific safeguards should begin. That leaves the G20 with the question of whether governments should avoid unnecessary regulation without waiting for a new AI capability to cause serious damage before creating rules for it. The answer could determine whether the Carolina Principles become a useful framework for AI governance or simply another point of disagreement between major economies.
Does less AI regulation mean faster innovation?
The argument behind the US position is that AI companies are developing systems faster than governments can write rules for them. Requiring a new regulatory process for every new application could create delays, raise costs and make it harder for smaller companies to compete. However, Stanford’s AI Index found that US federal agencies introduced 59 AI-related regulations in 2024, more than twice the number introduced in 2023. At the same time, AI adoption has expanded rapidly, with 78% of organizations reporting AI use in 2024, up from 55% a year earlier.
That suggests regulation and innovation are not moving in opposite directions. The question is whether governments can target rules at genuinely dangerous uses without putting unnecessary restrictions on ordinary AI development. Also, China is rapidly closing the gap with the US on AI model performance, while the US still has a major lead in private investment. If Washington believes regulation could weaken its lead, encouraging other countries to adopt a lighter framework could become part of the competition for AI dominance.
The outcome of whether other G20 members will sign on to the Carolina Principles or push for stronger safeguards could shape the direction of the wider debate ahead of the G20 leaders’ summit in Miami in December.
Meanwhile, European retailers are seeking changes to the European Union’s incoming artificial intelligence rules, arguing that AI-generated advertising content should not automatically fall under strict disclosure requirements designed to combat deceptive deepfakes
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