US Lawmakers Pivot to Sector-Specific AI Oversight
Washington, D.C. – In a significant shift for United States technology policy, Congressional leaders are moving away from broad pauses on artificial intelligence development, favoring a nuanced, sector-by-sector regulatory framework instead. Speaking at the Incompas Policy Summit this week, Rep. Jay Obernolte (R-Calif.) clarified the legislative path forward, signaling strong bipartisan support for targeted oversight that balances innovation with public safety.
For the AI industry, this marks a decisive transition from the uncertainty of potential development moratoriums to a more predictable, risk-based governance model. The emerging consensus suggests that future regulations will be tailored to specific use cases—such as healthcare or finance—rather than applying a blanket restriction on the technology itself.
The End of the Broad Moratorium
The concept of a general "AI Moratorium" gained headlines in 2025 when a provision to pause certain AI developments was attached to a budget reconciliation bill. However, Rep. Obernolte, Chairman of the House Science, Space and Technology Subcommittee on Research and Technology, has now characterized that effort as a strategic "messaging amendment" rather than a permanent policy goal.
"The moratorium was never intended to be a long-term solution," Obernolte told attendees at the summit. He explained that the provision, which passed the House before being stripped by the Senate, was designed to force a necessary conversation about the division of power between state and federal regulators. The shock of its passage in the House served its purpose: it highlighted the urgency for a cohesive national strategy to prevent a fractured landscape of conflicting state laws.
With that conversation now mature, lawmakers are discarding the blunt instrument of a moratorium in favor of precision tools. The focus has shifted to defining clear federal "lanes" that establish where national preemption is necessary to protect interstate commerce, while leaving room for states to act as "laboratories of democracy" in specific areas like child safety and government procurement.
How the Sector-by-Sector Model Works
The core of the new legislative framework is the recognition that not all AI carries the same risk profile. Treating a recommendation algorithm in a video game with the same scrutiny as an AI-powered diagnostic tool in a hospital is increasingly viewed as inefficient and stifling to innovation.
Obernolte illustrated this distinction using a medical analogy. "The FDA has already issued thousands of permits for the use of AI and medical devices," he noted. "There could be a model that is unacceptably risky in something like a pacemaker that's going to be implanted in someone's body, but completely benign in another deployment context."
Under the proposed sector-specific approach, individual federal agencies would be empowered to regulate AI within their own domains. This allows for deep, context-aware oversight:
- Healthcare: The FDA continues to manage AI in medical devices.
- Finance: The SEC and banking regulators oversee algorithmic trading and credit underwriting.
- Transportation: The DOT manages autonomous vehicle safety standards.
This method avoids the pitfalls of a "one-size-fits-all" law that could inadvertently cripple low-risk applications while failing to adequately police high-stakes systems.
Codifying CAISI: The Engine of Standardization
A central pillar of Obernolte’s proposal is the statutory codification of the Center for AI Standards and Innovation (CAISI). Formerly known as the U.S. AI Safety Institute under the previous administration, the body has been renamed and continued under President Trump.
Obernolte envisions CAISI not as a direct regulator, but as a technical resource hub—a "factory" that produces the measuring sticks and safety protocols other agencies need. CAISI’s mandate would include:
- Creating an inventory of technical tools and evaluation methodologies.
- Developing a "regulatory toolbox" of standards.
- Distributing these tools to sector-specific regulators (like the FDA or FAA) to implement within their jurisdictions.
By centralizing the technical expertise within CAISI while decentralizing the enforcement to sectoral agencies, Congress aims to create a system that is both scientifically rigorous and legally flexible.
Navigating the Federal-State Patchwork
One of the most pressing concerns for AI developers has been the rise of a "patchwork" of state-level regulations. Without a federal standard, companies potentially face 50 different compliance regimes. The new framework aims to resolve this through federal preemption, a stance supported by President Trump’s December 2025 Executive Order.
The Executive Order directed a review of state laws to identify those that impose undue burdens on AI developers. However, it also carved out specific exceptions where state regulation is encouraged.
Proposed Division of Regulatory Authority
| Regulatory Domain | Authority | Focus Area |
|---|---|---|
| Interstate Commerce | Federal (Preemptive) | Core AI model safety, interstate data traffic, fundamental rights protections. |
| Child Safety | State & Local | Protections for minors online, educational settings. |
| Infrastructure | State & Local | Zoning for data centers, energy usage, local compute infrastructure. |
| Procurement | State & Local | Rules governing how state agencies purchase and use AI tools. |
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Bipartisan Paths Forward
Despite the often polarized political climate in Washington, AI governance remains a rare area of cross-party collaboration. Obernolte emphasized that while the parties may disagree on broader issues, the work within the science and technology committees is "amazing how bipartisan things are."
To pass substantive legislation, the framework will need 60 votes in the Senate, necessitating a bill that appeals to both Republicans and Democrats. The sector-by-sector approach appears to be that compromise. It addresses Republican concerns about over-regulation by avoiding a central "AI Czar" or heavy-handed licensing regime, while satisfying Democratic priorities regarding safety and ethical standards through empowered agencies.
For Creati.ai readers and the broader AI community, this legislative pivot signals a maturing market. The era of existential debate regarding whether to pause AI is ending; the era of practical, industry-specific compliance is beginning. Developers should prepare for a regulatory environment that asks not if AI can be built, but how it fits safely into the specific sector it serves.
