What the New National AI Framework Means for Your Business
On March 20, 2026, the White House released its National Policy Framework for Artificial Intelligence (AI), a comprehensive legislative blueprint intended to guide future federal AI regulation. While the framework does not yet carry the force of law, it provides a clear signal of the administration’s regulatory direction and offers important insight into how the compliance landscape for artificial intelligence is likely to evolve. For organizations operating across multiple states, the framework is particularly significant because it points toward a more unified national approach that could eventually replace today’s fragmented state-by-state requirements.
State-Level AI Legislation and Compliance Challenges
Over the past two years, more than 1,500 AI-related bills have been introduced at the state level, addressing issues such as algorithmic bias, transparency, consumer disclosures, and the use of synthetic media. This growing patchwork has created meaningful compliance challenges for regional and national businesses, increasing costs and complicating AI adoption strategies. The administration’s framework explicitly characterizes AI development and deployment as “inherently interstate” and argues that inconsistent state regulation undermines U.S. competitiveness. As a result, the White House is urging Congress to adopt a light-touch, innovation-oriented federal regime that would preempt many state AI laws while preserving traditional state authority in areas such as law enforcement and zoning.
Federal Preemption and the Path Forward
The national AI framework builds on a December 11, 2025, executive order that directed federal agencies to identify state AI laws viewed as unduly burdensome and to consider litigation or funding-related mechanisms to address conflicts with federal priorities. If Congress ultimately acts on these recommendations, businesses operating in multiple jurisdictions could benefit from a single national baseline rather than navigating dozens of different state standards. That outcome, however, is neither immediate nor guaranteed, and the transition period is expected to be complex.
Rather than proposing a comprehensive regulatory structure similar to the European Union’s AI Act, the administration favors targeted federal rules focused on areas of heightened risk. These include child safety online, AI-generated digital replicas and deepfakes, critical infrastructure resilience and energy usage, and enforcement actions against AI-enabled fraud and impersonation scams. Notably, the framework leaves several contentious issues, such as whether training AI models on copyrighted material constitutes fair use, to existing law and the courts, signaling restraint in expanding regulation where legal doctrines are still developing.
Support for Small and Mid-Sized Businesses
The framework also places a strong emphasis on promoting AI adoption by small and mid-sized businesses. It calls on Congress to consider grants, tax incentives, and technical assistance programs designed to lower barriers to entry and encourage responsible AI deployment. Business advocacy groups have welcomed this aspect of the proposal, noting that regulatory consistency at the federal level would make it easier for smaller organizations to invest in AI tools without the disproportionate burden of monitoring and complying with divergent state regimes.
Addressing AI-Enabled Misconduct and Infrastructure Concerns
At the same time, the administration underscores the need for stronger enforcement against AI-enabled misconduct. The national AI framework highlights the growing prevalence of scams that leverage deepfake audio, video, and synthetic identities to target consumers and businesses, and it calls for enhanced law enforcement tools to address these risks. It also acknowledges concerns around the concentration of AI infrastructure, particularly large data centers, and emphasizes the importance of ensuring that local communities are not adversely affected through higher electricity costs or uneven economic benefits. Workforce development and infrastructure investment are positioned as key levers to ensure that AI-driven growth extends beyond major technology hubs.
From a compliance perspective, the framework does not change existing obligations in the near term. State AI and privacy laws remain fully enforceable, and businesses must continue to comply with the requirements of the jurisdictions in which they operate. Most legal commentators expect a multi-year period in which state regimes such as Colorado’s AI Act and emerging rules in California and New York coexist with ongoing federal debate. During this period, federal agencies, including a newly formed Department of Justice AI Litigation Task Force, are expected to scrutinize state laws that may conflict with federal objectives.
If Congress ultimately adopts broad preemption, multi-state organizations could see a meaningful reduction in long-term compliance complexity. Until that happens, however, companies should not pause current compliance efforts or delay governance initiatives in anticipation of federal relief. In fact, the national AI framework suggests that scrutiny of AI-enabled fraud, impersonation, and consumer harm is likely to intensify, particularly in sectors such as financial services, healthcare, and professional services. Organizations that rely on AI in customer interactions, decision-making, or payment processes should expect increased attention to their controls, monitoring practices, and incident response capabilities.
Best Practices for AI Governance and Vendor Management
In practical terms, the framework reinforces the importance of foundational AI governance. Businesses should have a clear understanding of where and how AI is used within their operations, including reliance on third-party tools embedded in core systems. Governance structures, even if modest in scale, should define accountability, approval processes, and ongoing review of AI systems for accuracy, bias, security, and regulatory compliance. Vendor management will also be critical, as contractual clarity around data usage, model updates, audit rights, and regulatory cooperation can significantly reduce risk in an environment where state and federal expectations may diverge.
Preparing for Future Federal AI Policy
The National Policy Framework for Artificial Intelligence makes clear that while sweeping federal regulation is not imminent, the direction of travel is toward greater consistency, targeted oversight, and stronger enforcement against misuse. Organizations that invest now in understanding their AI footprint, strengthening governance, and aligning controls with emerging best practices will be better positioned to adapt as federal policy takes shape.
How Our Firm Can Help
As the AI regulatory landscape continues to evolve, our firm can support clients with governance design, internal control documentation, vendor risk management, and readiness for AI-related incentives and reporting. If you would like to discuss how these developments may affect your organization or industry, we encourage you to contact your engagement team or the Information Systems and Risk Assurance team at BNN.
Disclaimer of Liability: This publication is intended to provide general information to our clients and friends. It does not constitute accounting, tax, investment, or legal advice; nor is it intended to convey a thorough treatment of the subject matter.