Article

Executive order highlights importance of AI governance

An agile AI governance framework is critical to navigating regulatory change

February 04, 2026

Key takeaways

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A recent executive order could be a powerful step toward a unified U.S. AI regulatory framework.

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The order proposes a nationwide approach to AI regulations instead of a patchwork system.   

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A robust AI governance strategy is crucial to deploy AI tools and navigate regulatory standards.

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As artificial intelligence tools become embedded in core business operations, regulatory guidance is beginning to shape how organizations design, deploy and govern these systems. On Dec. 11, 2025, President Trump signed Executive Order 14365, “Ensuring a National Policy Framework for Artificial Intelligence.” This is a notable early step in the drive for a unified regulatory framework for AI in the United States and presents potential changes in compliance standards for organizations building or deploying AI systems. 

Creating a federal standard for AI development and use

The administration has signaled the desire for one approach to AI regulations across the nation and not a patchwork of state laws. Further, the administration is pushing for any regulation to be "minimally burdensome" to avoid slowing down innovation and investment into AI by the private sector. To this end, it seeks to evaluate and potentially challenge any state laws as unconstitutional or in conflict with federal regulations, pushing for a new federal framework to supersede any state law once enacted.

The White House is analyzing any laws that impose “excessive regulation” or the alteration of the “truthful outputs” of AI models, using Colorado’s Senate Bill 24-205, also known as the Colorado Anti-Discrimination in AI law, as an example. That law was approved in 2024 and goes into effect Feb. 1, 2026.

The executive order contemplates restricting grant funding, specifically from the Broadband Equity Access and Deployment (BEAD) grant program, if state laws do not align. While executive orders do not have direct authority over states, non-alignment could lead to meaningful federal funding impacts.

Leveraging an AI governance framework

It is imperative for organizations to have a robust AI governance framework to thoughtfully implement and deploy AI tools, especially when navigating compliance amid a shifting regulatory landscape. Many organizations leverage the U.S. Department of Commerce’s National Institute of Standards and Technology’s (NIST) AI Risk Management Framework (RMF) as a starting point. RSM referenced the NIST AI RMF in the development of our Responsible AI Governance Framework, as well as elements of several additional leading resources.

The NIST AI RMF suggests evaluating AI systems for “harmful bias” and instituting an approach for bias management. Organizations must carefully weigh the goals and impacts of bias management, as currently defined, in their governance strategies as well as in the development and deployment of AI tools. More importantly, they must adapt those strategies to keep pace with this rapidly evolving field.

The takeaway

While Congress may take time to develop and pass a comprehensive national AI framework, your organization should not pause your own AI governance efforts. State laws and international regulations will continue to be introduced and modified, and AI governance should be thoughtfully incorporated into your organization’s risk management practices. AI regulation is shifting quickly, but so is AI capability. RSM’s investment in responsible AI, agentic workflows and modern digital platforms gives middle market leaders the structure they need to innovate with confidence.

Contact our team to learn more about the AI executive order and its potential effects on your organization, how to implement an effective governance framework, or how to successfully evaluate AI risk in your organization.

RSM contributors

  • john_huyett.jpg
    John Huyette
    Principal
  • Joseph Fontanazza
    Manager
  • Chris Henderson
    Chris Henderson
    Director

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