AI and the Role of the Board of Directors

Holly J. Gregory is a Partner and co-chair of the Global Corporate Governance practice at Sidley Austin LLP. This post is based on The Governance Counselor piece.

Artificial intelligence (AI) has the capacity to disrupt entire industries, with implications for corporate strategy and risk, stakeholder relationships, and compliance that require the attention of the board of directors.

In 1950, Alan Turing, the father of computer science, famously asked, “Can machines think?” Since then, the application of computer science and algorithms to collect and analyze data, identify patterns, make predictions, and solve problems has advanced significantly. Today’s AI has become much better at mimicking aspects of human intelligence, such as “understanding” language, “perceiving” images, or “generating” new, albeit derivative, content (generative AI). AI is also advancing in its ability to self- improve its own performance (machine learning). (For more on AI and machine learning, see Artificial Intelligence and Machine Learning: Overview on Practical Law; for more on key terms used in descriptions of AI, machine learning, and generative AI, see Artificial Intelligence Glossary on Practical Law.)

As a transformative technology, AI has the capacity to disrupt entire industries, creating new business opportunities and presenting new risks for companies. Companies also play a key role in AI-related research and development (R&D) and deployment, with the potential for considerable societal impact. Boards of directors and their advisors need to consider:

  • How AI is currently used by the company and its competitors.
  • How AI may disrupt the company’s business and industry.
  • The strategic implications and risks associated with AI products and services.
  • The impact of AI applications on the workforce and other stakeholders.
  • The implications for compliance with legal, regulatory, and ethical obligations.
  • The governance implications of the use of AI and related policies and controls.

Board responsibility for managing and directing the company’s affairs requires oversight of the exercise of authority delegated to management, including oversight of legal compliance and ethics and enterprise risk management. The board’s oversight obligations extend to the company’s use of AI, and the same fiduciary mindset and attention to internal controls and policies are necessary. Directors must understand how AI impacts the company and its obligations, opportunities, and risks, and apply the same general oversight approach as they apply to other management, compliance, risk, and disclosure topics.

This article sets out:

  • A three-part approach to aid corporate boards in their oversight of the company’s AI-related activities, including:
    •   understanding AI as a matter of corporate strategy and risk;
    • considering the impact of AI activities on employees, customers, other key stakeholders, and the environment; and
    • overseeing the company’s compliance with laws and regulations that are relevant to AI and the development of related policies, information systems, and internal controls.
  • Practice pointers and issues that boards and their advisors should consider in connection with AI.

Understanding AI as a Matter of Corporate Strategy and Risk

As with any emerging technology, AI presents opportunities for competitive advantage and innovation while also presenting significant potential for risks. Boards and corporate managers need to assess the impact of AI on corporate strategy and risk, and specifically consider:

  • How AI is currently used, for example, to support innovation and R&D, enhance customer experiences, manage the supply chain, reduce risk, or otherwise improve efficiency and reduce costs.
  • How AI may change the industry and the business.
  • Strategic opportunities AI presents that have not yet been captured.
  • Associated operational, financial, compliance, and reputational risks.

Boards should explore with management how to best use AI to help achieve business objectives, and further opportunities to capitalize on AI. Consideration should be given to how AI is likely to disrupt the industry in the future, implications for the current business model, and any changes needed for the company to capture opportunities to use AI for competitive advantage through innovation and the creation of new business models or revenue streams.

In addition to providing opportunities for competitive advantage, AI has the potential to both create and manage risk. On the risk creation side, AI systems are highly dependent on data, and there is a risk of bias and other errors with the data, the algorithm, or both that could lead to error and unintended outcomes. For example, the data may be biased by the way the information is obtained or used, and the algorithms may be biased due to erroneous assumptions in the machine learning process. High data dependency also gives rise to the risk of disputes over data rights, privacy violations, and cybersecurity breaches.

There is also considerable concern about how AI is being developed and deployed and whether it will harm society. At a recent Yale summit of CEOs, 42% indicated that they were concerned about the potentially catastrophic impact of AI (see Chief Executive, At Yale CEO Event Honoring Steven Spielberg, Little Consensus on AI Future). Boards need to understand the potential for AI-related risks and the systems in place to help manage and mitigate those risks, including systems to safeguard data, and ensure both that the AI systems are secure and that the company is in compliance with AI-related rules and regulations. (For more on AI risks, see What’s Market: Artificial Intelligence Risk Factors on Practical Law.)

On the risk management side, AI applications can help identify and mitigate risks. For example, AI has proven useful in the financial services industry for detecting credit card and other financial fraud, in cybersecurity defense by further automating vulnerability management and intrusion detection, and in compliance applications to identify a variety of policy violations.

In addition to categorizing various types of AI-related risks, the NIST AI Risk Management Framework describes four specific functions — govern, map, measure, and manage — to help organizations address AI risks. The “govern” function relates to cultivating and implementing a risk management culture and applies to all stages of an organization’s risk management. This function targets certain categories of outcomes set forth in abbreviated form below:

  • Policies, processes, procedures, and practices related to the mapping, measuring, and managing of AI risks are in place, transparent, and implemented effectively.
  • Accountability structures ensure appropriate teams and individuals are empowered, responsible, and trained for mapping, measuring, and managing AI risks.
  • Workforce diversity, equity, inclusion, and accessibility processes are prioritized in the mapping, measuring, and managing of AI risks.
  • Organizational teams are committed to a culture that considers and communicates AI risk.
  • Processes are in place for robust engagement with relevant AI actors.
  • Policies and procedures are in place to address AI risks and benefits arising from third-party software and data and other supply chain issues.(For more on the NIST framework, including its govern function, see NIST Releases Artificial Intelligence Risk Management Framework on Practical Law.)

Significant work is underway to help companies address AI-related risks. In January 2023, the US Department of Commerce’s National Institute of Standards and Technology (NIST) issued the Artificial Intelligence Risk Management Framework (AI RMF 1.0), which was developed with input from both the private and public sectors as a voluntary, flexible risk framework to “promote trustworthy and responsible development and use of AI systems.” The framework identifies characteristics of trustworthy AI systems, such as being “valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair with harmful bias managed.” Notably, NIST has called on companies to establish policies that define AI risk management roles and responsibilities, including for the board (see Box, NIST AI Risk Management Framework: Governance).

Considering the Impact of AI Activities

AI, and in particular generative AI, raises considerable concerns about the potential for misuse and unintended consequences. Boards and management teams need to consider the responsible corporate use of AI, and the potential impact on employees, customers, other key stakeholders, and the environment. Consideration should be given to avoiding and mitigating unintended consequences, including through the use of policies and internal controls overseen by the board or an appropriate board committee.

AI can provide efficiency with routine tasks and is improving in its ability to aggregate data, recognize patterns, and create content, with the prospect of freeing up employees to increase their focus on tasks that require judgment and creativity. AI’s growing potential to automate skilled tasks has implications for workforce training, management, and productivity. Boards should consider how the company’s use of AI is impacting employees and the talent pipeline, whether employees are being trained to use AI in a manner that leverages their skills and mitigates AI risks, and what types of policies should be implemented to encourage appropriate use of AI by employees for approved use cases — particularly in highly regulated or otherwise high-risk contexts, such as health care, financial services, or hiring and promotion decisions.

AI’s potential for perpetuating bias in the data sets on which it relies raises concerns about the use of AI in employment and promotion decisions. The board should understand whether and, if so, how the company uses AI for these purposes and what policies are in place regarding these uses. The use of AI in employment-related decisions may be subject to regulation, and regulation in this area is likely to expand. For example, New York City Local Law 144 of 2021 prohibits employers and employment agencies from using an “automated employment decision tool” unless the tool has been subject to a bias audit within the prior year, information about the bias audit is publicly available, and certain notices have been provided to employees or job candidates (N.Y.C. Admin. Code §§ 20-870 to 20-874; 6 RCNY §§ 5- 300 to 5-304 (rules implementing Local Law 144)). Enforcement of this law and related rules began on July 5, 2023.

In 2021, the Equal Employment Opportunity Commission (EEOC) announced an initiative aimed at ensuring AI tools used in employment decisions comply with the federal civil rights laws. The initiative includes gathering information about the adoption, design, and impact of AI technologies and issuing guidance for employers on AI use and algorithmic fairness. The EEOC also issued, in May 2023, technical assistance regarding AI and algorithmic decision-making tools and the potential for those tools to result in illegal discrimination under Title VII. This guidance focuses on disparate impact in employment selection processes. Additionally, state privacy laws (such as the California Consumer Privacy Act) and the EU General Data Protection Regulation apply to employee data and can add regulatory obligations around profiling and automated decision-making. (For more on using AI in employment decisions, see Artificial Intelligence (AI) in the Workplace on Practical Law.)

Boards should also understand how AI is used by customers and suppliers, as well as its impact on the environment. The use of AI is already well-embedded in various industries, such as the automotive, e- commerce, entertainment, financial services, health care, hospitality, insurance, logistics, manufacturing, marketing, retail, and transportation industries. Boards may not understand the ways in which their companies or others in their industries are using AI to interface with customers and suppliers, and the extent to which these uses involve data gathering, with privacy implications and related concerns about bias. Additionally, boards may not appreciate the environmental impact of, for example, training an algorithm to identify reliable patterns, which can require heavy energy use to analyze millions of data sets.

(For more on the potential legal issues surrounding AI, see Artificial Intelligence: Key Legal Issues in the January 2023 issue of Practical Law The Journal and see Artificial Intelligence Toolkit on Practical Law.)

Overseeing AI-Related Compliance and Controls

AI raises compliance issues that require board consideration. AI systems can incorporate bias and lack transparency, which may lead to concerns about equity and accountability. Additionally, AI systems are heavily reliant on data and often implicate privacy and data protection regulation. The use of AI — and generative AI in particular — may have implications for intellectual property (IP) protections.

Not surprisingly, AI is the focus of legislative and regulatory initiatives in the US and abroad. Boards need to understand and stay apprised of these developments and oversee the company’s compliance, as well as the development of relevant policies, information systems, and internal controls, to ensure that AI use is consistent with legal, regulatory, and ethical obligations, with appropriate safeguards to protect against potential risks (as discussed above). In doing so, they should be mindful of the variety of ways in which the company may face exposure to AI-related compliance and other risks, including through AI technology that is internally developed, licensed from others, or acquired through M&A activity.

AI-related regulation seeks to balance the interest in encouraging innovation with concerns about human rights and civil liberties, including privacy rights, anti-discrimination interests, consumer safety and protection, IP protection, information integrity, security, and fair business practices. Select regulatory developments in the US, EU, and UK are outlined below. (For more on key developments in AI regulation, see Trends in AI Regulation on Practical Law.)


A variety of legislative and regulatory activities at both the federal and state levels are in play. While there currently is no comprehensive AI regulation, US regulators have made clear that this is not an unregulated space. Significant developments include:

  • Enactment of the National Artificial Intelligence Initiative Act of 2020 (NAIIA). In the NAIIA, which was passed on January 1, 2021, Congress defined AI as a “machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations or decisions influencing real or virtual environments” (National Defense Authorization Act for Fiscal Year 2021, Div. E, § 5002(3)). The NAIIA provides for coordination across federal agencies to help accelerate AI research in promotion of economic prosperity and national security, and amends the NIST Act to include a mission to advance and support the development of AI standards. Overall, the approach appears to be one of encouraging investment and prudent risk management. (For more information, see New AI Initiative Act Sets Up National AI Initiative Office and Amends NIST Act on Practical Law.)
  • Federal agencies’ guidance and enforcement activities. Agencies including the Consumer Financial Protection Bureau (CFPB), Department of Justice (DOJ), Equal Employment Opportunity Commission (EEOC), Food and Drug Administration (FDA), Federal Trade Commission (FTC), and Securities and Exchange Commission (SEC) have issued guidance or otherwise indicated through enforcement activity that they view AI as within the purview of their current regulatory and enforcement authorities. For example:
  • The Blueprint for an AI Bill of Rights. This white paper, issued by the White House Office of Science and Technology Policy in October 2022, expresses a set of five principles and associated practices to help guide the design, use, and deployment of AI systems in a manner that protects the interests of individuals and communities.
  • Various proposed congressional bills and policy objectives. These include:
    • the Algorithmic Accountability Act of 2022 (H.R. 6580; S. 3572), which would require entities that use generative AI systems in making critical decisions pertaining to housing, health care, education, and employment, to assess potential bias and other impacts;
    • the DEEP FAKES Accountability Act of 2021 (H.R. 2395), which would require transparency about the creation and public release of false personations;
    • the Digital Services Oversight and Safety Act of 2022 (H.R. 6796), which would require transparency about misinformation created by generative AI; and
    • the SAFE Innovation Framework, proposed in June 2023 by Senator Schumer, which is intended to guide Senate efforts toward AI regulation and focuses on: (1) safeguarding national security and economic security for workers; (2) supporting the deployment of responsible systems to address concerns around misinformation and bias, IP concerns, and liability; (3) protecting elections and promoting societal benefits while avoiding potential harms; (4) determining what information the federal government and the public need to know about an AI system, data, or content; and (5) supporting US-led innovation in security, transparency, and accountability in a manner that unlocks the potential of AI and maintains US leadership in the technology.
  • State laws. State consumer protection laws, including privacy laws and prohibitions of unfair and deceptive business practices, are widely viewed as applying to AI. Additionally, a number of states (and local governments) have enacted or are considering specific legislation or regulation of AI.


In June 2023, the European Parliament passed the EU Artificial Intelligence Act (EU AI Act) to hold AI developers, providers, and users accountable for safe implementation. While additional steps are required before it becomes law, it would require, among other things, transparency regarding copyrighted material used in training an AI system and safeguards to prevent use of illegal content.

The EU AI Act builds on the European Commission proposal of a risk-based regulatory scheme that would define four levels of risk: unacceptable, high, limited, and minimal. Unacceptable risks are defined as AI uses that present a clear threat to the safety, livelihoods, and rights of people and will be banned. An example is the use of certain remote biometric identification systems in publicly accessible spaces for law enforcement purposes, except in limited cases. High-risk uses include AI uses that could put safety or health at risk, such as in some transportation or surgery applications, as well as uses that involve access to employment or education. High-risk AI will be subject to strict regulation to ensure adequate risk assessment and mitigation systems, high quality datasets, traceability of results, informed use and compliance, human oversight, and a high level of security and accuracy. (European Parliament, Briefing: EU Legislation in Progress: Artificial Intelligence Act (June 2023).)


In March 2023, the UK Department for Science, Innovation, and Technology published a white paper, AI Regulation: A Pro-Innovation Approach, with a proposal intended to encourage responsible innovation and reduce regulatory uncertainty through a principles-based approach that focuses on: (1) safety, security, and robustness; (2) transparency and “explainability”; (3) fairness; (4) accountability and governance; and (5) contestability and redress. UK regulators have been asked to consider how to implement these five principles within their specific sectors, and a public consultation closed June 21, 2023.

In March 2023, the UK Information Commissioner’s Office updated its Guidance on AI and Data Protection, including guidance on how to apply the principles of the UK’s General Data Protection Regulation to the use of information in AI systems.

Practice Pointers

As corporate use of AI expands, the board needs to understand the role of AI in the business and how it is integrated into decision-making processes. The board should also consider how AI can be used to support its own efforts, for example, its ability to collect and analyze data and identify trends that may improve financial projections and capital allocation decisions. AI may also help anticipate and identify potential risks, inform efforts to mitigate risks, and predict outcomes. AI may be used in information and reporting systems to identify matters for board attention in a more timely manner or otherwise used to improve the information available to the board.

Board oversight is key to ensuring that AI is used in a responsible and ethical manner in alignment with the company’s strategic objectives and values. This requires that board members understand how AI is used in the company and what potential opportunities and risks AI presents, including risks from algorithm and data bias. Mitigating these risks requires ensuring that the data used to train AI algorithms is diverse and representative, and that the algorithms themselves are transparent and explainable.

To effectively oversee the use of AI, the board should consider establishing clear reporting lines and metrics for measuring the effectiveness of AI, as well as ensuring that it receives regular updates on the company’s use of AI and any associated opportunities and risks. From a practical perspective, in approaching oversight of AI, directors can rely on the same fiduciary mindset and attention to internal controls and policies as they apply to other matters.

Together with its advisors, the board should consider a variety of AI-related issues. The board should ensure it has an adequate understanding of:

  • How the business and industry could be disrupted by AI, and what strategic opportunities and risks AI presents.
  • How AI is used in company processes and third-party products used by the company.
  • How the company is positioned to leverage its data assets, the risks that may stem from the use of data for the AI use cases, and management’s existing processes for tracking and protecting the data used to train or be fed into AI tools.
  • The AI governance system management has put in place, including whether the system has appropriate input from relevant business functions, IT, human resources, legal, risk, and compliance.
  • The company’s goals and why AI is the right tool for achieving them. In evaluating this issue, the board should seek management’s input on:
    • whether the company has the expertise and resources to pursue a strategy that relies on AI in a responsible way;
    • how resilient the company’s use of AI is in terms of cybersecurity, operations, and data access and management;
    • how success will be measured;
    • what proof of concept will look like, and how to test for efficacy and compliance as an AI initiative launches and as AI use develops over time;
    • what the key risks are and what risk mitigation tools are available; and
    • whether there are material disclosure considerations relevant to any audience (such as users, regulators, business partners, or shareholders).

The board should also evaluate:

  • The need for or outcome of discussions with management about the NIST AI Risk Management Framework and its application to the company.
  • Whether it has appropriate access to information, advice, and expertise on AI matters to be able to understand strategic opportunities and risks and consider related controls.
  • What additional steps should be taken to ensure that the board is kept appropriately informed on AI matters.
  • Whether management has identified:
    • risks to the business from AI; and
    • any mission-critical compliance or safety risks related to the company’s use of AI and, if so, discussed them with the board (these risks should be mapped to a board committee for more frequent and in-depth attention, and reflected in the committee charter, agenda, and minutes).
  • Whether the board (or the responsible board committee):
    • appropriately reflects AI issues on its agenda;
    • is regularly updated about rapidly emerging legislative and regulatory developments related to the use of AI;
    • has reviewed the company’s policies and procedures concerning the use of AI;
    • has considered, together with management, the implications of AI for the company’s cybersecurity, privacy, and other compliance policies and controls programs;
    • has discussed with management the potential for misuse and unintended consequences from the company’s use of AI with respect to employees, customers, other key stakeholders, and the environment, and how to avoid or mitigate those risks;
    • understands the extent to which AI is used in tracking and assessing employee performance, and has ensured that controls are in place to foster compliance with any relevant regulation;
    • understands who in the company is responsible for monitoring AI use, and AI-specific compliance and risk management, and how the company ensures compliance with AI-specific requirements, such as “secure by design” requirements; and
    • oversees the company’s policies and procedures related to the use of generative AI, including whether those policies and procedures consider the potential for bias, inaccuracy, breach of privacy, and related issues of consumer protection, cyber and data security, IP protection, and quality control.
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