The US government's intervention in Anthropic's model release has established a new regulatory playbook that OpenAI is now preemptively adopting. This signals a shift toward government-gated AI deployment, where companies seek federal approval before releasing powerful new models to a select group of trusted partners.

Despite media reports, the idea of an "FDA for AI" that pre-approves models is not supported by key policy advisors. Insiders stress the goal is industry coordination to harden government systems against AI threats, not to create a Washington-based approval bottleneck that would kill innovation.

After industry pushback, the White House has clarified it is not pursuing a new, FDA-style bureaucracy for AI model approval. Instead, the administration is focusing on direct, ongoing collaboration with major AI labs to mitigate extreme risks before models are released, favoring a flexible partnership over rigid regulation.

As the capability gap between internal and public models widens, the most critical decisions about safety will be made pre-release. This internal frontier lacks a governance framework, as current regulations are only triggered by public deployment.

The Trump administration's consideration of an FDA-like review process for new AI models signals a trend towards "soft nationalization." This involves government agencies partnering with and overseeing top AI labs to mitigate catastrophic risks and maintain a national security advantage.

OpenAI's policy blueprint diverges from the broad preemption in the Obernolte-Trahan bill. The company supports preempting state laws only on "the same frontier safety risks," a more targeted approach. This signals a strategic preference for focused federal oversight rather than a blanket ban on state-level regulation.

Instead of establishing clear regulations, the White House is intervening directly in AI rollouts, limiting access to new models like OpenAI's on a case-by-case basis due to national security. This high-touch approach gives the government immense control but creates uncertainty and is viewed by some safety advocates as a 'worst of both worlds' scenario.

Instead of an outright ban on models like China's Kimi K3, the US government is more likely to use "soft law" tactics. This involves pressuring chokepoints like US-based data centers and hyperscalers to restrict the hosting and deployment of these foreign models.

Demis Hassabis's detailed AI regulation plan includes requiring labs to submit frontier models for testing up to 30 days before release. This would apply to all models deployed in the US, including foreign and open-source ones, while exempting smaller, non-frontier models from the rule.