Karsten Wenzlaff, Advisor
August 26th, 2025
Karsten Wenzlaff is a Crowdfunding and Fintech Expert from Germany. He is Secretary-General of Digit[...]
US AI Framework Targets To Limit State Rule
Mar 23, 2026 | NCFA Insight | AI Policy And Regulation
Washington Signal One National Approach to AI
On Mar 20 2026, the White House released a national AI policy framework and legislative recommendations that asks Congress to build a single federal approach to AI and limit conflicting state laws. Washington looks to reduce regulatory fragmentation before state level AI rules harden into a patchwork. The framework isn't law but a blueprint for Congress to show where U.S. AI policy is heading and what type of rules the White House thinks are needed to support large scale use of artificial intelligence across the economy.
Federal Preemption Sits At The Center
The document argues that state by state AI rules can impose uneven burdens on firms trying to build and deploy AI systems nationally. The White House position is that Congress should set the main framework and stop conflicting state rules from slowing deployment. At this point, it's less about creating a new AI regulator and more about stopping fifty different rulebooks from becoming the default U.S. model.
The framework highlights six areas: child protection, energy and electricity costs, intellectual property, free expression, public education and workforce readiness, and maintaining U.S. leadership in AI.
Policymakers want to lower friction for deployment while demonstrating that safety and public concerns are still being addressed. It's a delicate balance because it tells the market what the White House sees as the main tradeoff. The focus is not on building a heavy new AI rule set, but rather on enabling scale, lowering infrastructure bottlenecks, and avoiding fragmented oversight.
See: Pro Human AI Declaration Gains Backing Across Sectors
AI is already proliferating across lending, fraud detection, compliance, payments, customer operations, and model driven decisioning. A patchwork of state by state compliance would raise cost, slow deployment, and make national rollout harder for both incumbents and startups.
A single federal framework wouldn't solve every issue. Questions around accountability, model assurance, liability, and sector specific supervision would still remain. But it would remove a major barrier by making it easier to roll out AI across the United States.
How This Differs From The UK And Canada
The U.S. approach is mainly about fragmentation. The White House wants one national frame instead of competing state level rules.
The UK conversation is more operational. The FCA’s Mills Review asks how AI could impact retail financial services through 2030 and beyond. Industry responses focus more directly on deployment barriers inside finance, including data access, Digital ID, payments infrastructure, and rulebook friction.
Canada is taking a broader path. The federal government’s AI strategy process gathered input from more than 11,000 Canadians and 28 task force members, with stronger emphasis on trust, safety, responsible adoption, and national direction. NCFA has already flagged the execution risk in this approach in its analysis of Canada’s AI strategy and capital flight risk.
The difference is important. The U.S. is trying to stop fragmentation. The UK is pressing on execution barriers. Canada is still nuturing national direction. Each approach points to a different policy priority and will result in a different speed of deployment and potential competitive advantage (or disadvantage).
See: AI Ethics, State Power, And The Fight Over RedLines
Jurisdictions that reduce friction and create usable operating environments will attract more investment, deployment, and talent. Jurisdictions that let regulatory complexity pile up will throttle adoption even when the technology is ready.
Takeaway
The White House's AI policy framework makes the federal direction clearer. The U.S. is trying to stop state level fragmentation before it becomes the default AI regime. It's important for fintechs and financial services because the level of scale, cost, and deployment speed depends heavily on whether one federal rulebook replaces fifty competing ones.
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