The White House's proposed legislative framework explicitly recommends against creating a new, overarching federal body to regulate AI. Instead, it advocates for empowering existing agencies with subject-matter expertise (e.g., in finance or healthcare) to develop and enforce AI rules within their own domains, suggesting a decentralized approach to governance.

Major government action on AI is unlikely to be driven by political shifts like midterm elections. Historical precedent suggests a high-salience incident will be the necessary trigger for significant, bipartisan regulatory intervention, regardless of which party controls the government.

The US President's move to centralize AI regulation over individual states is likely a response to lobbying from major tech companies. They need a stable, nationwide framework to protect their massive capital expenditures on data centers. A patchwork of state laws creates uncertainty and the risk of being forced into costly relocations.

Because a deadlocked federal Congress struggles to pass novel legislation, national regulatory frameworks for AI remain unlikely in the short term. Meaningful political pushback will instead originate at the state and municipal level, driven by community resistance to physical data centers, AI-powered surveillance cameras, and school district battles over student devices.

Investors should not over-react to congressional turbulence. Many of the most market-relevant policies—on trade, regulation, industrial strategy, and AI—are executed via executive authority, not congressional action. This means their trajectory is unlikely to be altered by events like a shutdown or shifting political dynamics in Congress.

While national security framing around competition with China protects AI compute from federal halts, key operational bottlenecks sit below Washington. Crucial approvals like interconnection, large-load electricity tariffs, zoning, water permits, and tax abatements are governed by states, public utility commissions, and local officials. Consequently, governors' races and utility boards matter more for data center timelines and build-out durability than congressional control.

The growing consensus in Congress for AI regulation is driven less by national security or abstract safety concerns and more by the pragmatic fear of massive job displacement in their home districts. This political reality is creating unlikely bipartisan alliances focused on mitigating the economic disruption of AI.

Facing a federal vacuum on AI policy, major players like OpenAI and Google are surprisingly endorsing state-level regulations in California and New York. This counter-intuitive move serves two purposes: it creates a manageable, de facto national standard they can influence, and it pressures a gridlocked Congress to finally act to avoid a messy patchwork of state laws.

Expect AI legislation to be a series of targeted, incremental bills rather than one sweeping law. Congress will address specific issues like model transparency and intellectual property while engaging in international diplomacy and observing state-level experiments.