BSA Unveils "Preempt With Precision" Strategy to Harmonize US AI Regulation

As the United States enters 2026, the artificial intelligence policy landscape faces a critical juncture. With rapid AI adoption across industries clashing with a growing patchwork of state-level regulations, the Business Software Alliance (BSA) has introduced a targeted legislative framework designed to bridge the divide. Dubbed "Preempt With Precision," the proposal offers a strategic pathway for Congress to establish national standards while respecting the historical role of state governance.

The proposal comes at a moment of heightened urgency. Following an executive order signed by President Trump in December 2025—which sought to challenge state laws governing AI—the tension between federal inaction and state aggression has peaked. Major states, including California and New York, have already enacted significant legislation targeting frontier AI models, creating a complex compliance environment for developers and enterprises. The BSA’s framework suggests that a blanket federal takeover is unnecessary, arguing instead for a surgical approach where federal law supersedes state regulations only on specific, congressionally addressed issues.

The Growing Divide: State Initiatives vs. Federal Stagnation

The urgency for a cohesive national strategy is driven by the acceleration of state-level policymaking. Without a comprehensive federal law, states have moved to fill the regulatory vacuum, resulting in what industry observers fear is a fragmented "patchwork" of rules that could stifle innovation.

California has led this charge with the enactment of Senate Bill 53, a landmark law focusing on "frontier AI models"—the most advanced systems capable of broad tasks. The bill mandates rigorous safety assessments, public documentation, and incident reporting. Similarly, New York has passed the Responsible AI Safety and Education (RAISE) Act, with upcoming amendments expected to align it closely with California’s standards. Other states, including Colorado and Washington, are actively revising or advancing their own AI governance bills.

While these state efforts reflect a proactive approach to safety, they present a significant challenge for national security and economic uniformity. The BSA argues that inconsistent regulations across state lines create barriers to entry for AI adoption and complicate the compliance landscape for businesses operating nationwide.

A Surgical Approach to Federal Preemption

The core of the BSA's "Preempt With Precision" strategy is a simple yet powerful principle: When Congress acts to establish a national approach for a specific AI issue, that federal approach should preempt state laws addressing the same issue.

This nuances the traditional debate between "total preemption" (where federal law wipes out all state AI laws) and "no preemption" (where states are free to legislate regardless of federal action). By focusing on targeted preemption, the BSA aims to create a "safe harbor" for innovation in areas where a unified national standard is most critical, such as national security and high-risk model safety, while leaving other areas to state jurisdiction.

According to Craig Albright, Senior Vice President of US Government Relations at BSA, this approach is designed to foster bipartisan consensus. "The best way to remove barriers to AI innovation and adoption is through federal legislation grounded in areas of consensus," Albright noted. By narrowing the scope of preemption to specific, agreed-upon frameworks, lawmakers may avoid the legislative gridlock that often plagues broader tech regulation efforts.

Case Study: Frontier Model Safety

The most immediate application of this precision strategy focuses on frontier AI models. These advanced systems, which underpin the current generative AI boom, carry risks that transcend state borders, particularly regarding national security and the potential proliferation of weapons of mass destruction (WMD).

Under the BSA's proposal, Congress would establish a national framework for frontier model safety that includes:

• Mandatory Obligations: Requirements for developers to implement safety frameworks and disclose relevant information for models posing "covered risks."
• Voluntary Disclosures: Expectations for transparency that go beyond mandatory minimums.
• State Safe Harbor: Provisions that protect companies complying with the federal standard from duplicative or conflicting state transparency obligations.

This approach acknowledges that issues like national security are inherently federal responsibilities. A patchwork of state-level safety protocols for frontier models could inadvertently create security vulnerabilities or contradictory compliance requirements that hamper the US's ability to maintain a competitive edge in AI development.

Defining the Boundaries: State vs. Federal Authority

A key component of the "Preempt With Precision" framework is the recognition that states retain a vital role in protecting their citizens. The strategy does not propose stripping states of their authority to regulate in areas where they have historical expertise, such as consumer protection and labor rights.

The following table outlines the proposed division of regulatory labor under the BSA's framework:

Proposed Division of AI Regulatory Authority

The Path Forward for 2026

As 2026 unfolds, the pressure on Congress to act is mounting. The Biden Administration’s previous executive orders set the stage for measurement science and standards, but the legislative branch has yet to codify these into permanent law. President Trump’s recent executive actions indicate a willingness to use executive power to force harmonization, but a legislative solution is widely viewed as more durable and legally sound.

The "Preempt With Precision" framework offers a pragmatic compromise. It allows Republicans, who generally favor preemption and business certainty, to achieve a unified market for AI. Simultaneously, it allows Democrats, who often champion state-level protections, to preserve the ability of states like California to lead on consumer and labor issues.

"AI developers, the businesses that want to adopt AI, and consumers who want assurances that AI is being developed and used responsibly are not well-served by a piecemeal and patchwork approach," Albright stated.

By focusing on specific, high-stakes issues like frontier model safety, Congress has an opportunity to pass meaningful legislation this year. The success of this strategy will depend on whether lawmakers can agree on the definitions of "frontier models" and the specific risks that warrant federal intervention. If successful, 2026 could mark the year the United States finally moves from a reactive, fragmented regulatory environment to a proactive, unified national AI strategy.