As we settle into September, the Diligent Market Intelligence (DMI) research team has for months been focused on compiling the thousands of investor voting records from the previous proxy season. The annual wave of N-PX filings is a key point in our calendar year where we typically collect over 60% of our data as investment funds work to submit the key regulatory documents by the end-of-August deadline set by the Securities and Exchange Commission (SEC).

While mutual funds and other registered investment companies have long been required to report their votes, this year opens up a new reporting requirement for hedge funds and others to report their compensation-related votes. The move has led to a dramatic increase in filings with almost 11,000 at the time of writing compared to approximately 2,600 at the same point last year.

Under the new regime, the new cohort of N-PX filers are required to report how they voted proxies on:

• “say on pay”
• “say on frequency”
• golden parachute compensation in connection with a merger or acquisition.

DMI is collecting all of these new data points, as well as new disclosure on the number of shares voted, which we are working to make available to clients from the end of September.

Company officers and their advisors will likely benefit from the new transparency by identifying investors which had not publicly shared grievances, especially those with a mixed record of activism and passive investment. For instance, of the nearly 5,000 compensation-related votes logged by D.E. Shaw Group, 12% were logged against management recommendations.

And it will shine a light on where activists are supportive of at least some elements of their targets’ governance. Of Trian’s nine votes over the last year, the only vote against management’s recommendation was against Disney’s “say on pay” resolution.

This has all been made possible with an expanded team of DMI experts spread across multiple time zones who have to date sprinted to import a staggering 19,673,775 N-PX votes using an automated collection process.

“We have been examining the new format since May in preparation and filings have been coming in since July 1 and will continue through early September,” said DMI’s Sophie Miles, who heads up the marathon effort for the research team. “This year, the new 13F filers will see our workload significantly increase as we anticipate about 8,000 additional filings to come in compared to about 2,500 in previous years.”

To date, filings from just shy of 3,000 investors, 11,000 funds and over 22,000 issuers have been imported for processing by DMI.

"All of our 

 module clients are eagerly awaiting this data to complete their proxy season reviews and uncover new and unique insights that the new disclosures afford. Our dedicated support team will be ready to see to the demands for a variety of custom requests," Miles concluded. 

New N-PX Disclosure Requirements: What it all means

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.

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