As the European Union unites its 27 nations under the 

, regulations on the other side of the Atlantic are following a different path as the United States pursues a patchwork of federal, state and industry frameworks. Compliance and oversight have become more complicated than ever.

Unlike the EU, the United States does not have a regulatory body specific to artificial intelligence. In lieu of an overarching authority, entities throughout government and industry have responded with their own guidance, seemingly at the speed of ChatGPT itself.

In October 2022, the White House released its 

 through its Office of Science and Technology and issued an 

 one year later. In February 2024, Securities and Exchange Chair Gary Gensler put out a call for 

. And these are just a few of many laws, policies, frameworks and more that are emerging.

Here, we provide an overview of AI regulations in the U.S., diving deeper into the following topics:

How is AI defined in the U.S. and what is the scope for regulation?

How to stay ahead as the AI regulatory landscape in the U.S. evolves

To move these principles into practice in an organization’s own operations, it’s helpful to understand what is, and isn’t, considered AI in the United States.

Fortunately, the White House Executive Order provides guidance here. It defines AI as:

Any data system, software, hardware, application, tool or utility that operates in whole or in part using AI

With the ability to make predictions, recommendations or decisions

With an influence on real or virtual environments

Territorial and sectoral scope of AI regulations

Organizations will need to prepare to comply with U.S.-based AI regulations if the organization’s operations include:

Sectors such as financial and lending services, healthcare and education that deal in large amounts of data, complex processes requiring automation and complex analysis

Moreover, it's prudent for all organizations, regardless of their geographical location or sector, to prepare for compliance with some form of regulatory requirements around the use of AI. As AI technology continues to advance and integrate into various aspects of business operations, regulatory bodies worldwide are increasingly focusing on ensuring that these technologies are used ethically and responsibly.

The current state of AI regulations in the U.S.

As a result of this decentralized governance approach, organizations now have AI guidance — both mandated and voluntary — from a variety of sources, which bring a rich array of perspectives to apply to their own unique situations and technology applications. “It’s about understanding the use cases in your organization and how are you going to have that oversight,” said Vice President of Product Management at Diligent, 

But there’s a downside, as well. Organizations also have to deal with a host of disparate rules and regulations, each with their own limitations and all bearing the potential for overlap and conflicts when considered en masse.

What this means for boards and executives

How can boards and executives navigate this growing labyrinth, so new regulations, requirements and risks don’t catch them by surprise? Here are a few foundational frameworks, as well as policies in development, to keep in mind.

8 principles for responsible AI development and deployment in the U.S.

Even as AI is a technological innovation running on models, algorithms and analytics, the U.S. approach to AI governance puts humans — and human decision-making — at the center of it all. “In the end, AI reflects the principles of the people who build it, the people who use it, and the data upon which it is built,” the White House’s Executive Order declares.

 on the Safe, Secure and Trustworthy Development and Use of Artificial Intelligence lists eight key principles for the responsible development and deployment of AI for workers:

Companies should design, develop and train AI in a way that protects workers.

Companies should inform and give employees genuine input in the design, development, testing, training, use and oversight of AI systems.

Companies should use AI systems to assist, complement and enable workers and improve job quality.

AI systems should not violate or undermine workers’ rights.

Companies should support workers during AI-related job transitions.

AI systems should have clear governance systems, evaluation processes and human oversight.

Companies should be transparent in their AI use.

What’s next for federal AI legislation in the U.S.?

AI has swiftly become a regular consideration across federal policy, especially when this policy involves national security, the supply chain and innovation. The 

, which allocates billions to the semiconductor industry, lists AI among its key technology areas, with a charge to 

 that is “safe, secure, fair, transparent and accountable, while ensuring privacy, civil rights and civil liberties.”

In 2024, bipartisan efforts have been proliferating in Congress to shape and regulate AI across government and life. A bipartisan bill to boost the nation’s 

 and a subcommittee examining standards and policies for 

As these laws take shape, federal agencies are crafting their own AI governance, driven by an official mandate to put the White House’s Executive Order’s eight key principles outlined above into action. At every U.S. agency, working groups are evaluating the development and use of AI, developing regulations and identifying opportunities for engagement with the private sector, with timelines and objectives outlined in the Executive Order itself.

Compliance considerations for AI use in the U.S.

Compliance is challenging when dealing with a work in progress — but it’s a challenge organizations dealing with American-made AI systems or using AI in their U.S. operations must accept.

What should you keep in mind as AI regulations in the U.S. evolve?

Human-centered transparency and accountability: 

Is the AI system designed with human-defined objectives for AI decision-making?

 Does the AI system explain how these decisions are made

Different sectors will have mandates tailored to specific AI concerns, such as 

 for industries like healthcare that collect personal information and 

 for industries like financial services that involve qualifying for a mortgage or loan.

Fortifying your risk management and enforcement policies

As AI regulations in the U.S. continue to take shape, it’s also important to get your compliance program in place. This includes:

Who’s responsible for AI systems and oversight?

 What does, and does not, qualify as AI in your organization?

 How will you identify, address and mitigate AI-related risk?

If you spot a potential violation of the AI rules, like abusive data practices. What happens next?

But federal policies are just one part of the picture for AI regulations in the U.S.

In addition to the many activities by the executive and legislative branches, AI regulations in the U.S. also involve state and local rules. Just a few examples include:

 regulating automated decision-making and the use of customer data

An artificial intelligence bill of rights in 

The AI Digital Replica Protections Law in 

Staying ahead of AI regulations in the U.S.: The critical role of leadership

Directors and executives play a critical role in shaping the strategic direction and ethical foundation of their organizations. As AI continues to transform industries worldwide, the regulatory landscape surrounding AI is also evolving rapidly — with the U.S. regulatory landscape being particularly difficult to keep up with. It's essential for leaders to stay informed about these changes to ensure compliance, mitigate risks and leverage AI opportunities responsibly.

To help face this challenge, the Diligent Institute curated their 

AI Ethics & Board Oversight Certification course

. This certification equips leaders with the necessary tools and knowledge to stay on top of AI regulations in the U.S. and make ethical and informed decisions, ensuring their organizations navigate AI complexities with integrity and compliance.

AI regulations in the U.S.: Navigating a complex and evolving landscape

Siemens Financial Services Inc. (SFS, Inc.), the financing arm of Siemens, has successfully embraced a transformative approach to control monitoring through the implementation of Diligent’s innovative solutions. By leveraging Diligent’s tools, SFS, Inc. has achieved continuous assurance across its operations, significantly enhancing its financial control framework and driving efficiency in compliance processes.

The collaboration between SFS, Inc. and Diligent illustrates how the integration of digital solutions can address critical challenges in regulatory compliance, particularly in the context of internal controls over financial reporting (ICFR).

Addressing key challenges with continuous control monitoring

Within the financial services industry, SFS, Inc. faced the mounting challenge of tightening European regulations, necessitating a shift from traditional, manual control processes to more efficient, automated systems.

The organization's operations, spread across 14 countries, were hindered by repetitive manual control activities, leading to inefficiencies and a higher risk of errors. As the business continued to expand, these manual processes proved increasingly unsustainable, highlighting the urgent need for a robust solution.

 emerged as an integral piece of SFS, Inc.’s strategy to mitigate these issues. By transitioning to an automated control framework, SFS, Inc. was able to streamline operations, reduce the burden of manual tasks and enhance overall control effectiveness. The move to CCM was driven by the necessity to replace labor-intensive manual processes with technology, thus aligning with the company’s broader digital transformation goals.

Diligent’s ACL Analytics enabled some of our core competencies to flourish and to use some innovative ways of adding value in a new way that was both effective and efficient.          — Jason A. Gross, CPA, CIA, CFE, CISA, ACDA, Vice President of Controls Management at SFS, Inc.

The automation provided by Diligent not only addressed the inefficiencies inherent in manual controls but also allowed SFS, Inc. to handle increased business complexities and portfolio growth more effectively. This transition facilitated a shift in focus from time-consuming, repetitive tasks to more strategic activities, maximizing the use of limited resources both qualitatively and quantitatively.

Additionally, the positive feedback from external auditors reinforced the value of this transformation, validating the shift towards continuous monitoring to maintain rigorous compliance standards.

The impact of introducing ACL Analytics on ICFR controls

Diligent’s advanced solutions have profoundly enhanced the Internal Controls over Financial Reporting (ICFR) at Siemens Financial Services Inc. One of the standout features of Diligent’s approach is its capacity to evaluate the entirety of transactional data, moving beyond the limitations of traditional sampling techniques. This comprehensive scrutiny ensures a more rigorous and accurate assessment of control effectiveness, significantly mitigating the risk of undetected errors or inconsistencies.

The introduction of Diligent’s automated tools has led to a remarkable 

90% reduction in the time needed for ICFR testing

. This substantial time saving allows SFS, Inc. to reallocate resources more strategically, enhancing the efficiency and focus of their compliance efforts. The shift from manual to automated testing processes means that SFS, Inc. can now conduct thorough, real-time reviews, which bolster the reliability and integrity of their financial reporting mechanisms.

In addition to time efficiencies, the implementation of Diligent’s solutions has also resulted in a 

50% reduction in the occurrence of exceptions

. The decrease not only signifies improved compliance but also underscores the robustness of SFS, Inc.'s financial controls.

Achieving early efficiency gains through digital transformation

The digital transformation at Siemens Financial Services Inc. has catalyzed notable early efficiency gains, with the help of 

. By digitizing control processes, SFS, Inc. has enhanced its compliance framework and significantly improved its operational agility. The shift to automated systems has enabled the company to streamline previously cumbersome manual tasks, thereby allowing staff to focus on more strategic initiatives that drive business growth and competitiveness.

 helps SFS, Inc. effectively monitor and manage data quality and user access across multiple applications, ensuring robust oversight and compliance. This integration facilitates real-time issue identification and resolution, contributing to a more proactive and responsive control environment. Furthermore, the platform’s advanced analytics capabilities provide valuable insights, enabling informed decision-making and better risk management practices.

The transformation has not only reduced the time and resources required for compliance activities but has also fostered a culture of transparency and accountability within the organization. As SFS, Inc. continues to navigate the complexities of the financial services industry, the efficiencies gained from this digital transformation position the company to adapt swiftly to changing regulatory landscapes and market conditions, ensuring sustained growth and competitive advantage.

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