AMPLIFY  VOL. 38, NO. 4
  

AI has the potential to significantly transform many aspects of corporate activity, including decision-making, productivity, customer experience, and content creation. The impact on boardrooms is likely to be significant — but perhaps in different ways than is commonly recognized.

Boards are aware of the enormous potential of AI. According to one survey, corporate leaders rank “increasing the use of AI across the organization” above all other priorities for the coming year, including such staples as revenue growth, productivity, margin improvement, and strategic opportunities. Boards have also been busy determining the organizational use of AI, its competitive impact, level of financial investment, training, guidelines, and reputational risk.¹

Much less consideration has been paid to the ways the application of AI can reshape the operations and practices of the board itself, with the prospect of substantially improving corporate governance quality. Four areas in particular are poised for impact:

• How boards function

• How boards process information

• How boards interact with management, and management with boards

• How board advisers contribute

Although AI has the potential to dramatically alter board practices, its adoption also raises important questions about how to maintain the line between board and managerial responsibilities, as well as how expectations on each side will change.

Traditional View of Governance

Effective corporate governance relies on the separation of managerial and board responsibilities. Management runs the corporation, and the board oversees management to ensure its actions are in the interest of shareholders. In the absence of red flags, the board is permitted to rely on information provided by management to inform its decisions and carry out this oversight role.² Because the board is not involved in day-to-day operations, an information asymmetry exists between what the board and management know about the organization. In some situations, this information asymmetry can be severe.

Current board practices reflect how boards operate under this constraint. Management presents information through regularly scheduled board meetings, committee meetings, and ad hoc communications. Boards respond to this information by asking questions and requesting additional information as needed. For some matters, the board contracts with a third party (e.g., consultant, banker, auditor) to provide market information or an external perspective on best practices. Under this arrangement (assuming the board makes decisions with due deliberation and without conflict of interests), it will have satisfied its fiduciary duty to shareholders.

Unfortunately, plenty of examples point to the insufficiency of this arrangement. Many boards have been woefully uninformed about the financial, operating, and strategic risk of management decisions — as borne out by repeated examples of corporate meltdowns over the years. Boards have erred in situations of CEO selection, financial reporting, product liability, compensation setting, and reputation management. One study underscored a surprising disconnect between the information board members say are important drivers of corporate performance and the information and metrics boards actually receive to monitor this performance. Although the proximate cause of the failure identified in the study was the choice of KPIs, the fundamental problem is an issue of information flow between management and the board.

Impact of AI on Governance

AI has the potential to change this dynamic. First, it can increase the volume, type, and quality of information available to management and boards. By making this information readily available, it reduces information asymmetry between management and directors. Board members are much less likely to be “in the dark” about the operating and governance realities of their companies because technology makes it easier for them to search and synthesize public and private information made available to them through AI board tools.

Second, AI increases the burden on both parties to review, synthesize, and analyze information prior to board meetings. Managers and directors can expect to spend more time on meeting preparation because the quantity of available knowledge is substantially greater. Elementary information that was previously reviewed during meetings will be expected to be analyzed and digested before the meeting.³

Third, AI allows for the supplementation (and, in some cases, replacement) of information provided by third-party advisers and consultants. Furthermore, AI can increase the breadth of analysis available to the board, coupling the retrospective review of mostly historical data (prevalent today) with more powerful tools for predictive and trend analysis. These tools will allow boards to be more proactive and less reactive.

At the same time, the adoption of AI in the boardroom will raise significant questions. The most important is about expectations for board contribution. Current governance practice generally places board members in a responsive position to management and the information it provides (the type, structure, and framing of this information).⁴ With AI, directors will have access to information that is orders of magnitude beyond management-prepared board materials. AI tools can prompt board members with key questions based on the agenda and suggest analyses that could help reach a decision, such as benchmarking against competitors or linking data to reveal trends. Expectations for a director’s diligence in reviewing and preparing this information will be exponentially higher, and the quality of questions, challenges, and insights should be correspondingly higher.

Of course, executives will have the opportunity to try out their presentations on an AI interface that can prepare them for the questions they should expect. By (confidentially) asking, “What are the greatest weaknesses in the arguments I have made?” and “What are the potential flaws in my proposal?” executives should be better positioned to anticipate and respond to challenges raised by their boards.

A related question is about possible limits to the information boards should/will have access to. In theory, granting directors access to an AI interface that has full access to all data in the corporate data repository means directors have no limit (relative to management) to the information they can access. From a legal perspective, however, boards might not want unrestricted access. Where and how to draw the line (and what information is ring-fenced) requires careful thinking. Boards and their counsel will have to establish protocols about how the board would rely on, for example, AI analysis conducted by an individual director (not provided by management). The impact this will have on fiduciary expectations is unknown.⁵

Furthermore, protection of this data from cybersecurity threats must be a central consideration. Given the sensitivity and proprietary nature of the data fed into AI models, significant steps should be taken to protect against unauthorized access. The risk will be higher for large corporations with multiple connection points to suppliers, customers, and employees.

Application to Governance Functions

AI also has the potential to alter the process by which boards fulfill specific governance obligations:

• Strategy. AI will allow boards and management richer access to scenario planning, assumption testing, risk identification, and investment prioritization. Some of the work that was previously outsourced to strategy consultants will be available in-house, at a lower cost and turnaround time. Boards will be able to compare AI’s recommendations against those of external strategy consultants.

• Compensation. The compensation committee will have access to analytical and benchmarking tools to evaluate compensation design against a more flexible set of peer institutions. Rather than waiting for external consultants to rerun analyses against predesignated peer groups, boards, and their advisers will be able to analyze the sensitivity of pay to peer groups selection in real time, predict proxy adviser recommendations, and consider tax and legal implications. This is especially plausible because public compensation data is already available in electronic form.⁶

• Human capital management. AI tools will let boards perform advanced analytics on information in the company’s human capital management databases, apply pattern recognition to workforce data, identify skills gaps, and perform long-range workforce and diversity forecasting.

• Audit. The audit committee will have access to surveillance tools that look for internal control weaknesses and identify potential fraud. The external auditor will also have access to AI tools that can provide reasonableness checks on a broader scope of transactions. The audit committee will have to consider the risks and ethical considerations of automating the audit process, including how and when to apply human judgment to a more automated process.

• Legal. AI technology will enable monitoring and summarization of emerging legal and regulatory developments, including lawsuits and enforcement actions at other corporations that might have a bearing on the company’s activities. Directors will have access to alternative legal opinions and cases in real time.

• Board evaluations. AI can also be leveraged to track, review, and analyze board effectiveness, at both the individual and board levels. AI-driven coaching and advisory tools will be able to replace work that is currently performed through survey forms, helping boards measure their engagement, evaluate how they allocate their time and focus, and determine whether they are primarily reactive or proactive.⁷

A significant portion of this analysis is likely to supplant or supplement work currently performed by paid advisers.

Additional Benefits & Risks

As AI is introduced to the boardroom, boards will be able to conduct real-time analysis led by management, advisers, or board members themselves. Alternative or supplemental information that is missing can be searched for and brought in during the discussion. This will increase the cadence of meetings and reduce decision-making delays, as less time is needed to wait on analysis conducted “between meetings.” This will allow for more robust scenario planning and potentially richer suggestions. Management will benefit from more sophisticated meeting preparation. They will be able to run simulation tests of their own presentations and ask AI to pose tough questions.

The application of this technology to the boardroom poses potential risks and challenges, however. One challenge is overcoming the wedge created between companies operating in an environment where competitors are predominantly private versus publicly traded. Public companies are subject to extensive disclosure requirements, and information about their operations and performance is publicly available. Private companies operate with fewer disclosure requirements. Depending on their competitive set, companies will have to think differently about the information they feed into models and how to perform benchmarking analysis using public, audited data versus privately sourced data that may carry inaccuracies or biases.

Another major risk is the substantial number of errors generated by current AI models. AI models come with inherent biases, the quality and availability of data can vary, and competitive intelligence may introduce additional complexities. AI makes computational and mathematical errors. It also does not always say “I don’t know” to questions it might not know an answer to, instead grabbing available data that’s not directly applicable to answer a question. Boards and managers must learn how to fact-check AI output before relying on it. This will require deeper (human) familiarity with the data. Boards will need to be educated on these and other limitations of this technology.⁸ 

AI monitoring will also likely generate a high number of red flags related to internal and external practices or threats. Boards will have to consider materiality risk in determining which risks require additional investigation, how to prioritize them, and how not to create a paper trail that increases the board’s liability.

With the cost of analysis dramatically reduced, board members will have to train themselves not to fall victim to excessive analysis (“analysis paralysis”) and stay focused on practical and efficient outcomes that benefit the corporation and its stakeholders. To this end, board and committee chairs will need to exhibit strong leadership skills to manage meeting dynamics effectively and ensure that analyses and conversations remain on track.

Conclusion: Why This Matters

As AI enters the boardroom, its influence will extend far beyond technology adoption — reshaping governance roles, decision-making dynamics, and expectations for both directors and managers:

• AI offers the potential to transform many corporate practices, including corporate governance. With the adoption of this technology in the boardroom, directors will essentially have a real-time adviser at hand. This will reduce information asymmetries between the board and management, allowing directors to be more proactive in identifying matters requiring attention. It also has the potential to significantly increase the time requirements of director and committee membership, as directors review, test, and synthesize information made available to them. They will need to ask: How will AI change board processes, practices, and dynamics? Are current directors equipped to adapt to this change? What training, resources, advice, and counsel will be needed to navigate it? How can directors embrace a larger role in analysis and decision-making without increasing their personal liability?

• AI will offer benefits to managers in their interaction with boards. Managers will effectively have a real-time board member by their side who can help them prepare for meetings, identify issues, and anticipate questions. Directors who do not contribute sufficiently will likely become more exposed. Companies will need to ask: How will managers react to a governance setting in which boards have more access and transparency into internal operations? How will directors respond to a setting in which technology interfaces can replicate many of their insights? Will AI in the boardroom lead to a general improvement in governance quality, or will failures of human and technological judgment continue to produce the same frequency of breakdowns that we witness today?

• Finally, companies must consider these crucial questions: At what point does a director’s access to extensive AI-driven information and analysis begin to blur the line between governance and management? Who will ensure that directors do not overstep their role by asking questions that encroach on managerial responsibilities?

Editor's note: This article was adapted from “The Artificially Intelligent Boardroom,” part of the Closer Look series published by the Corporate Governance Research Initiative at the Stanford Graduate School of Business, in collaboration with the Hoover Working Group on Corporate Governance and the Rock Center for Corporate Governance at Stanford University.

References

¹  Larcker, David F., Amit Seru, and Brian Tayan. “The Artificially Intelligent Boardroom.” Harvard Law School Forum on Corporate Governance, 8 April 2025.

²  Practical Law Corporate & Securities. “Fiduciary Duties of the Board of Directors.” Stanford Law School, 2023. 

³  This expectation is counter to that promised by commercial vendors. For example, in its marketing materials for AI board preparation technology, one company promises that AI will “supercharge meeting prep … uncover how AI can turn hours of preparation into instant insights, delivering smart questions and ready-to-use data in seconds.” In reality, companies that significantly increase information flow to directors report that it increases meeting prep time by raising expectations regarding the level of director preparedness. See: Larcker, David F., and Brian Tayan. “Netflix Approach to Governance: Genuine Transparency with the Board.” Stanford Graduate School of Business, May 2018; and Lim, Phil. “Using AI for Enhanced Decision-Making: 9 Innovative Ways to Boost Board Efficiency and Effectiveness.” Diligent, 24 July 2024. 

⁴  Baum, Alex, et al. “Building a Better Board Book.” Stanford Graduate School of Business, October 2017.

⁵  Directors are required to act with reasonable care in discharging their duties, including the obligation to make inquiries when confronted with red flags. A director conducting his/her own “research” through AI analysis may uncover activities or decisions that warrant further scrutiny. Failure to make inquiries might introduce legal complexities.

⁶  For example, the compensation data firm Equilar offers an AI-powered proxy analysis tool called ERIC (Equilar Research Intelligence Copilot) that facilitates extraction and analysis of proxy data, including compensation data; see: “Equilar Introduces ERIC, an AI-Powered Proxy Analysis Tool.” Press release, Equilar, 18 June 2024. 

⁷  Several tools available today use AI bots to record and summarize board meetings in real time; see: “AI Meeting Minutes Generator: The Future of Efficient Note-Taking.” HR Future, accessed 2025.

⁸  Computational and mathematical errors introduce potentially systemic issues, including in the areas of transportation, logistics, supply chain, capital markets, healthcare diagnoses, and natural disaster predictions.

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